diff --git a/.github/workflows/json-bundle.yml b/.github/workflows/json-bundle.yml
new file mode 100644
index 000000000..413b1d895
--- /dev/null
+++ b/.github/workflows/json-bundle.yml
@@ -0,0 +1,52 @@
+name: Bundle JSON files
+on:
+  push:
+    branches:
+    - main
+
+jobs:
+  bundle:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: 'read'
+      id-token: 'write'
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python 3.12
+        uses: actions/setup-python@v3
+        with:
+          python-version: '3.12'
+
+      - uses: getsentry/action-setup-venv@v1.0.4
+        id: venv
+        with:
+          python-version: '3.12'
+          cache-dependency-path: |
+            docs/tool/vdb_table/requirements.txt 
+          install-cmd: pip install -r docs/tools/vdb_table/requirements.txt 
+
+      - name: Generate bundle
+        id: bundle
+        run: |
+          python docs/tools/vdb_table/data_utils.py json_to_bundle -dd "docs/tools/vdb_table/data/*"
+
+      - id: 'auth'
+        uses: 'google-github-actions/auth@v2'
+        with:
+          workload_identity_provider: 'projects/903342166386/locations/global/workloadIdentityPools/github-pool/providers/github-provider'
+          service_account: 'github-actions-sa@superlinked-vectorhub.iam.gserviceaccount.com'
+    
+      - id: 'upload-bundle'
+        uses: 'google-github-actions/upload-cloud-storage@v2'
+        with:
+          path: './bundle.json'
+          destination: 'vectorhub-bundle/vectorhub-bundle'
+
+      - id: 'upload-schema'
+        uses: 'google-github-actions/upload-cloud-storage@v2'
+        with:
+          path: 'docs/tools/vdb_table/vendor.schema.json'
+          destination: 'vectorhub-bundle/vendor.schema.json'
\ No newline at end of file
diff --git a/.github/workflows/json-validate.yml b/.github/workflows/json-validate.yml
index 7a2fdb84c..2f98f4229 100644
--- a/.github/workflows/json-validate.yml
+++ b/.github/workflows/json-validate.yml
@@ -18,5 +18,5 @@ jobs:
         uses: GrantBirki/json-yaml-validate@v2.4.0
         with:
           base_dir: docs/tools/vdb_table/data
-          json_schema: docs/tools/vdb_table/data/vendor.schema.json
+          json_schema: docs/tools/vdb_table/vendor.schema.json
           json_schema_version: "draft-2020-12"
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 000000000..d558a0306
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,2 @@
+venv/
+.env
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/activeloop.json b/docs/tools/vdb_table/data/activeloop.json
new file mode 100644
index 000000000..4a1738365
--- /dev/null
+++ b/docs/tools/vdb_table/data/activeloop.json
@@ -0,0 +1,153 @@
+{
+  "name": "Activeloop Deep Lake",
+  "links": {
+    "docs": "https://docs.activeloop.ai/",
+    "github": "https://github.com/activeloopai/deeplake",
+    "website": "https://www.activeloop.ai/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/97",
+    "poc_github": "https://github.com/davidbuniat",
+    "slug": "activeloop"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "https://github.com/activeloopai/deeplake",
+    "comment": "https://github.com/activeloopai/deeplake"
+  },
+  "license": {
+    "value": "MPL 2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "python",
+      "c++"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 7200,
+  "vector_launch_year": 2023,
+  "metadata_filter": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "",
+    "source_url": "https://docs.activeloop.ai/performance-features/querying-datasets/query-syntax",
+    "comment": "While you can run embedding search + contains(text, 'keywoard') or multiple those (keyword search inside text tensor) since BM25 not available I wouldn't call a full hybrid search.  https://docs.activeloop.ai/performance-features/querying-datasets/query-syntax"
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": "although doable with UDFs and location storage"
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "https://docs.activeloop.ai/technical-details/data-layout",
+    "comment": "https://docs.activeloop.ai/technical-details/data-layout"
+  },
+  "sparse_vectors": {
+    "support": "partial",
+    "source_url": "https://docs.deeplake.ai/en/latest/Htypes.html",
+    "comment": "no native sparse vector support, although it supports all numpy arrays hence can also store sparse numpy arrays"
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "partial",
+    "source_url": "",
+    "comment": "you can search i.e. search keywords with TQL/SQL contains(...) function, but I assume you mean more than just text search, by full-text search engine"
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "https://docs.activeloop.ai/quickstart",
+    "comment": "https://docs.activeloop.ai/quickstart#creating-your-first-vector-store"
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "https://python.langchain.com/docs/integrations/vectorstores/activeloop_deeplake",
+    "comment": "https://python.langchain.com/docs/integrations/vectorstores/activeloop_deeplake"
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "https://docs.llamaindex.ai/en/stable/examples/vector_stores/DeepLakeIndexDemo.html",
+    "comment": "https://docs.llamaindex.ai/en/stable/examples/vector_stores/DeepLakeIndexDemo.html"
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "https://www.activeloop.ai/pricing/ Free up to 200GB, then $100 per 30M embeddings (200GB) https://www.activeloop.ai/resources/deep-lake-hnsw-index-rapidly-query-35-m-vectors-save-80/",
+    "source_url": "https://www.activeloop.ai/pricing/",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "https://docs.deeplake.ai/en/latest/deeplake.html",
+    "comment": "create a dataset per tenant, similar to collections/namespaces"
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://docs.activeloop.ai/performance-features/index-for-ann-search",
+    "comment": "Custom Memory optimized HNSW that sits on top of an object storage (including FS)"
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "partial",
+    "source_url": "https://docs.activeloop.ai/technical-details/data-layout",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/anariai.json b/docs/tools/vdb_table/data/anariai.json
new file mode 100644
index 000000000..17a4bb4d3
--- /dev/null
+++ b/docs/tools/vdb_table/data/anariai.json
@@ -0,0 +1,152 @@
+{
+  "name": "Anari AI",
+  "links": {
+    "docs": "",
+    "github": "https://github.com/Anari-AI",
+    "website": "https://anari.ai/vector-acceleration-engine/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/99",
+    "poc_github": "https://github.com/jovan-stojanovic",
+    "slug": "anariai"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Proprietary",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      ""
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 2023,
+  "metadata_filter": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/apachecassandra.json b/docs/tools/vdb_table/data/apachecassandra.json
new file mode 100644
index 000000000..4398e2592
--- /dev/null
+++ b/docs/tools/vdb_table/data/apachecassandra.json
@@ -0,0 +1,152 @@
+{
+  "name": "Apache Cassandra",
+  "links": {
+    "docs": "https://cassandra.apache.org/doc/latest/cassandra/vector-search/overview.html",
+    "github": "https://github.com/apache/cassandra",
+    "website": "https://cassandra.apache.org/_/Apache-Cassandra-5.0-Moving-Toward-an-AI-Driven-Future.html",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/84",
+    "poc_github": "https://github.com/jbellis",
+    "slug": "apachecassandra"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "java"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 8400,
+  "vector_launch_year": 2023,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": "via CassIO"
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "https://cassio.org/",
+    "comment": "via CassIO"
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": "via keyspaces and tables"
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://cassandra.apache.org/doc/latest/cassandra/developing/cql/indexing/sai/sai-faq.html",
+    "comment": "SAI index"
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/apachesolr.json b/docs/tools/vdb_table/data/apachesolr.json
new file mode 100644
index 000000000..4b3c94d44
--- /dev/null
+++ b/docs/tools/vdb_table/data/apachesolr.json
@@ -0,0 +1,152 @@
+{
+  "name": "Apache Solr",
+  "links": {
+    "docs": "https://solr.apache.org/guide/solr/latest/query-guide/dense-vector-search.html",
+    "github": "https://github.com/apache/solr",
+    "website": "https://solr.apache.org/guide/solr/latest/query-guide/dense-vector-search.html#usage-as-re-ranking-query",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/78",
+    "poc_github": "https://github.com/alessandrobenedetti",
+    "slug": "apachesolr"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "java"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 905,
+  "vector_launch_year": 2022,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "https://solr.apache.org/guide/solr/latest/query-guide/dense-vector-search.html",
+    "comment": "https://solr.apache.org/guide/solr/latest/query-guide/dense-vector-search.html#usage-with-filter-queries"
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "https://sease.io/2023/10/apache-lucene-solr-ai-roadmap-do-you-want-to-make-it-happen.html",
+    "comment": "https://sease.io/2023/10/apache-lucene-solr-ai-roadmap-do-you-want-to-make-it-happen.html linear combination implemented"
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "",
+    "source_url": "https://pypi.org/project/eurelis-langchain-solr-vectorstore/",
+    "comment": "https://pypi.org/project/eurelis-langchain-solr-vectorstore/"
+  },
+  "llamaindex": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "https://www.searchstax.com/lp/managed-solr-search",
+    "comment": "via https://www.searchstax.com/lp/managed-solr-search and https://bonsai.io"
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "https://issues.apache.org/jira/browse/SOLR-16836",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/aperturedb.json b/docs/tools/vdb_table/data/aperturedb.json
new file mode 100644
index 000000000..661591fe6
--- /dev/null
+++ b/docs/tools/vdb_table/data/aperturedb.json
@@ -0,0 +1,152 @@
+{
+  "name": "ApertureDB",
+  "links": {
+    "docs": "https://docs.aperturedata.io/",
+    "github": "https://github.com/aperture-data",
+    "website": "https://www.aperturedata.io/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/95",
+    "poc_github": "https://github.com/luisremis",
+    "slug": "aperturedb"
+  },
+  "oss": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      ""
+    ],
+    "source_url": "",
+    "comment": ""
+  },
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+    "comment": ""
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+}
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diff --git a/docs/tools/vdb_table/data/azureai.json b/docs/tools/vdb_table/data/azureai.json
new file mode 100644
index 000000000..25f62f7cf
--- /dev/null
+++ b/docs/tools/vdb_table/data/azureai.json
@@ -0,0 +1,152 @@
+{
+  "name": "Azure AI Search",
+  "links": {
+    "docs": "https://learn.microsoft.com/en-us/azure/search/",
+    "github": "https://github.com/Azure",
+    "website": "https://azure.microsoft.com/en-us/products/ai-services/ai-search/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/88",
+    "poc_github": "https://github.com/farzad528",
+    "slug": "azureai"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Proprietary",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      ""
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 2023,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "https://learn.microsoft.com/en-us/azure/search/hybrid-search-overview",
+    "comment": "https://learn.microsoft.com/en-us/azure/search/hybrid-search-overview"
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "https://learn.microsoft.com/en-us/azure/search/search-query-odata-geo-spatial-functions",
+    "comment": "https://learn.microsoft.com/en-us/azure/search/search-query-odata-geo-spatial-functions"
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "https://learn.microsoft.com/en-us/azure/search/vector-search-how-to-query?tabs=query-2023-11-01%2Cfilter-2023-11-01",
+    "comment": "https://learn.microsoft.com/en-us/azure/search/vector-search-how-to-query?tabs=query-2023-11-01%2Cfilter-2023-11-01#vector-query-request"
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "https://learn.microsoft.com/en-us/azure/search/index-ranking-similarity",
+    "comment": "https://learn.microsoft.com/en-us/azure/search/index-ranking-similarity"
+  },
+  "full_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "https://learn.microsoft.com/en-us/azure/search/cognitive-search-custom-skill-web-api",
+    "comment": "Custom Web API skill in skillsets - Azure AI Search | Microsoft Learn https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/announcing-the-public-preview-of-integrated-vectorization-in/ba-p/3960809"
+  },
+  "embeddings_image": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "Pricing - Azure Cognitive Search",
+    "source_url": "https://azure.microsoft.com/en-us/pricing/details/search/",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "https://learn.microsoft.com/en-us/azure/search/search-modeling-multitenant-saas-applications",
+    "comment": "https://learn.microsoft.com/en-us/azure/search/search-modeling-multitenant-saas-applications"
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "https://learn.microsoft.com/en-us/azure/search/search-capacity-planning",
+    "comment": "https://learn.microsoft.com/en-us/azure/search/search-capacity-planning#concepts-search-units-replicas-partitions-shards"
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 2048,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/chroma.json b/docs/tools/vdb_table/data/chroma.json
new file mode 100644
index 000000000..e3c5ed05e
--- /dev/null
+++ b/docs/tools/vdb_table/data/chroma.json
@@ -0,0 +1,152 @@
+{
+  "name": "Chroma",
+  "links": {
+    "docs": "https://docs.trychroma.com/",
+    "github": "https://github.com/chroma-core/chroma",
+    "website": "https://www.trychroma.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/79",
+    "poc_github": "https://github.com/jeffchuber",
+    "slug": "chroma"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "python"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 9700,
+  "vector_launch_year": 2022,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/clickhouse.json b/docs/tools/vdb_table/data/clickhouse.json
new file mode 100644
index 000000000..f3c8158a9
--- /dev/null
+++ b/docs/tools/vdb_table/data/clickhouse.json
@@ -0,0 +1,152 @@
+{
+  "name": "ClickHouse",
+  "links": {
+    "docs": "https://clickhouse.com/docs/knowledgebase/vector-search",
+    "github": "https://github.com/ClickHouse/ClickHouse",
+    "website": "https://clickhouse.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/100",
+    "poc_github": "https://github.com/cwurm",
+    "slug": "clickhouse"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache 2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "c++"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 32000,
+  "vector_launch_year": 2022,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "https://clickhouse.com/use-cases/machine-learning-and-data-science",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "https://clickhouse.com/docs/knowledgebase/filtered-aggregates",
+    "comment": "You can filter on a distance and aggregate or yes you can segment using If combinators."
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "",
+    "comment": "easily done by adding them as separate columns for each. e.g. CREATE TABLE titleVec Array(Float32), contentVec Array(Float32), title String, contentString ENGINE=MergeTree ORDER BY tuple()"
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "partial",
+    "source_url": "https://clickhouse.com/docs/en/sql-reference/functions/udf",
+    "comment": "possible to load an embedding model as a UDF"
+  },
+  "embeddings_image": {
+    "support": "partial",
+    "source_url": "",
+    "comment": "possible to load an embedding model as a UDF"
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "Clickhouse Pricing",
+    "source_url": "https://clickhouse.com/pricing",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "https://github.com/chdb-io/chdb",
+    "comment": "possible via https://github.com/chdb-io/chdb"
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "https://clickhouse.com/docs/en/operations/access-rights",
+    "comment": "with RBAC and row-level security"
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://clickhouse.com/docs/en/engines/table-engines/mergetree-family/annindexes",
+    "comment": "Via Usearch"
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "",
+    "comment": "sharding applicable to both vector and index storage"
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/cratedb.json b/docs/tools/vdb_table/data/cratedb.json
new file mode 100644
index 000000000..2dad1fcee
--- /dev/null
+++ b/docs/tools/vdb_table/data/cratedb.json
@@ -0,0 +1,152 @@
+{
+  "name": "CrateDB",
+  "links": {
+    "docs": "https://cratedb.com/solutions/vector-database",
+    "github": "https://github.com/crate/crate",
+    "website": "http://www.cratedb.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/98",
+    "poc_github": "https://github.com/marijaselakovic",
+    "slug": "cratedb"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "https://github.com/crate/crate",
+    "comment": "https://github.com/crate/crate"
+  },
+  "license": {
+    "value": "Apache 2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "java"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 3800,
+  "vector_launch_year": 2023,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "https://cratedb.com/docs/crate/reference/en/5.5/general/builtins/scalar-functions.html",
+    "comment": "combine knn_match with other criteria"
+  },
+  "hybrid_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "https://cratedb.com/docs/crate/reference/en/5.5/general/builtins/aggregation.html",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "https://cratedb.com/docs/crate/reference/en/5.5/general/dql/geo.html",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "https://cratedb.com/docs/crate/reference/en/5.5/general/ddl/data-types.html",
+    "comment": "add more columns of type knn_vector"
+  },
+  "sparse_vectors": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "https://cratedb.com/docs/crate/reference/en/5.5/general/dql/fulltext.html",
+    "comment": "based on Apache Lucene"
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "https://github.com/crate-workbench/langchain",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "https://console.cratedb.cloud/",
+    "comment": "https://console.cratedb.cloud/"
+  },
+  "pricing": {
+    "value": "CrateDB Pricing https://console.cratedb.cloud/",
+    "source_url": "https://cratedb.com/product/pricing",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "https://cratedb.com/docs/crate/reference/en/5.5/admin/privileges.html",
+    "comment": "via Schemas, Tables"
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://cratedb.com/blog/guide-to-write-operations-in-cratedb",
+    "comment": "all tables and columns in CrateDB are stored in lucene indexes/segments on disk. \nhttps://cratedb.com/blog/guide-to-write-operations-in-cratedb"
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "https://cratedb.com/docs/crate/reference/en/5.5/general/ddl/sharding.html",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 2048,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/datastaxastra.json b/docs/tools/vdb_table/data/datastaxastra.json
new file mode 100644
index 000000000..86cf9e1ef
--- /dev/null
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new file mode 100644
index 000000000..457ecdf3f
--- /dev/null
+++ b/docs/tools/vdb_table/data/elasticsearch.json
@@ -0,0 +1,152 @@
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diff --git a/docs/tools/vdb_table/data/epsilla.json b/docs/tools/vdb_table/data/epsilla.json
new file mode 100644
index 000000000..d2bf8c925
--- /dev/null
+++ b/docs/tools/vdb_table/data/epsilla.json
@@ -0,0 +1,152 @@
+{
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+  "links": {
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+    "website": "https://epsilla.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/89",
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+    "comment": "https://epsilla-inc.gitbook.io/epsilladb/vector-database/create-a-new-table#embedding-fields"
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+  "sparse_vectors": {
+    "support": "full",
+    "source_url": "https://epsilla-inc.gitbook.io/epsilladb/vector-database/dense-vector-vs.-sparse-vector",
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diff --git a/docs/tools/vdb_table/data/gcpvertexai.json b/docs/tools/vdb_table/data/gcpvertexai.json
new file mode 100644
index 000000000..9cf92c012
--- /dev/null
+++ b/docs/tools/vdb_table/data/gcpvertexai.json
@@ -0,0 +1,152 @@
+{
+  "name": "GCP Vertex AI Vector Search",
+  "links": {
+    "docs": "https://cloud.google.com/vertex-ai/docs/vector-search/overview",
+    "github": "https://github.com/GoogleCloudPlatform",
+    "website": "https://cloud.google.com/blog/products/ai-machine-learning/vertex-matching-engine-blazing-fast-and-massively-scalable-nearest-neighbor-search",
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\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/kdbai.json b/docs/tools/vdb_table/data/kdbai.json
new file mode 100644
index 000000000..87af019ef
--- /dev/null
+++ b/docs/tools/vdb_table/data/kdbai.json
@@ -0,0 +1,152 @@
+{
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+  "links": {
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diff --git a/docs/tools/vdb_table/data/lancedb.json b/docs/tools/vdb_table/data/lancedb.json
new file mode 100644
index 000000000..f4ded1e3b
--- /dev/null
+++ b/docs/tools/vdb_table/data/lancedb.json
@@ -0,0 +1,152 @@
+{
+  "name": "LanceDB",
+  "links": {
+    "docs": "https://lancedb.github.io/lancedb/",
+    "github": "https://github.com/lancedb/lancedb",
+    "website": "https://lancedb.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/87",
+    "poc_github": "https://github.com/changhiskhan",
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+    "source_url": "",
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+    "support": "full",
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+  "embeddings_text": {
+    "support": "full",
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+    "comment": "Embeddings from any provider can be run as a background process so that the user doesn't need to manually ingest them.\nhttps://lancedb.github.io/lancedb/embeddings/embedding_functions/"
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+  "disk_index": {
+    "support": "full",
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\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/marqo.json b/docs/tools/vdb_table/data/marqo.json
new file mode 100644
index 000000000..d4d4942ca
--- /dev/null
+++ b/docs/tools/vdb_table/data/marqo.json
@@ -0,0 +1,152 @@
+{
+  "name": "Marqo",
+  "links": {
+    "docs": "https://docs.marqo.ai/",
+    "github": "https://github.com/marqo-ai/marqo",
+    "website": "http://marqo.ai/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/73",
+    "poc_github": "https://github.com/OwenPendrighElliott",
+    "slug": "marqo"
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+    "comment": ""
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+    "comment": ""
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+    "source_url": "",
+    "comment": ""
+  },
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+    "source_url": "",
+    "comment": "via weights"
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+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
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+    "source_url": "",
+    "comment": ""
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+    "comment": ""
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+    "source_url": "",
+    "comment": ""
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+    "comment": "supports CLIP, OpenCLIP and Multilingual CLIP (as well as BYO models for these APIs)"
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\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/meilisearch.json b/docs/tools/vdb_table/data/meilisearch.json
new file mode 100644
index 000000000..e27296675
--- /dev/null
+++ b/docs/tools/vdb_table/data/meilisearch.json
@@ -0,0 +1,152 @@
+{
+  "name": "Meilisearch",
+  "links": {
+    "docs": "https://www.meilisearch.com/docs",
+    "github": "https://github.com/meilisearch/meilisearch",
+    "website": "https://www.meilisearch.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/93",
+    "poc_github": "https://github.com/gmourier",
+    "slug": "meilisearch"
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+  "oss": {
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+  "license": {
+    "value": "MIT",
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+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "rust"
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+  "metadata_filter": {
+    "support": "full",
+    "source_url": "https://solr.apache.org/guide/solr/latest/query-guide/dense-vector-search.html",
+    "comment": "Dense vector search"
+  },
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+    "support": "none",
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+    "comment": ""
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+  "facets": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "https://www.meilisearch.com/docs/learn/fine_tuning_results/geosearch",
+    "comment": "https://www.meilisearch.com/docs/learn/fine_tuning_results/geosearch"
+  },
+  "multi_vec": {
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+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
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+    "comment": ""
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+    "source_url": "https://www.meilisearch.com/pricing",
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+  },
+  "in_process": {
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\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/milvus.json b/docs/tools/vdb_table/data/milvus.json
new file mode 100644
index 000000000..ae5b9fbc7
--- /dev/null
+++ b/docs/tools/vdb_table/data/milvus.json
@@ -0,0 +1,153 @@
+{
+  "name": "Milvus",
+  "links": {
+    "docs": "https://milvus.io/docs",
+    "github": "https://github.com/milvus-io/milvus",
+    "website": "http://milvus.io/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/71",
+    "poc_github": "https://github.com/Enwei%20Jiao",
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+  "oss": {
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+    "comment": ""
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+    "comment": ""
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+    "source_url": "",
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+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/mongo.json b/docs/tools/vdb_table/data/mongo.json
new file mode 100644
index 000000000..c3177393f
--- /dev/null
+++ b/docs/tools/vdb_table/data/mongo.json
@@ -0,0 +1,153 @@
+{
+  "name": "MongoDB Atlas",
+  "links": {
+    "docs": "https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/",
+    "github": "https://github.com/mongodb",
+    "website": "https://www.mongodb.com/products/platform/atlas-vector-search",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/72",
+    "poc_github": "https://github.com/dvsander",
+    "slug": "mongo"
+  },
+  "oss": {
+    "support": "none",
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+    "comment": ""
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+    "comment": ""
+  },
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+    "comment": ""
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+    "source_url": "",
+    "comment": ""
+  },
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+    "comment": ""
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+    "source_url": "",
+    "comment": ""
+  },
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+    "comment": ""
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+    "comment": ""
+  },
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+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "MongoDB Pricing",
+    "source_url": "https://www.mongodb.com/pricing",
+    "comment": ""
+  },
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+    "source_url": "",
+    "comment": ""
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+    "support": "full",
+    "source_url": "",
+    "comment": "via logical partitioning or metadata"
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+    "support": "full",
+    "source_url": "https://www.mongodb.com/docs/atlas/atlas-search/faq/",
+    "comment": "https://www.mongodb.com/docs/atlas/atlas-search/faq/#does-fts-store-my-entire-index-in-memory-"
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
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+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
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+    "unlimited": false,
+    "source_url": "",
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+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/myscale.json b/docs/tools/vdb_table/data/myscale.json
new file mode 100644
index 000000000..a671b1e39
--- /dev/null
+++ b/docs/tools/vdb_table/data/myscale.json
@@ -0,0 +1,152 @@
+{
+  "name": "MyScale",
+  "links": {
+    "docs": "https://myscale.com/docs/en/vector-search/",
+    "github": "https://github.com/myscale",
+    "website": "https://myscale.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/101",
+    "poc_github": "https://github.com/lqhl",
+    "slug": "myscale"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Proprietary",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "c++"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 2023,
+  "metadata_filter": {
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+    "comment": ""
+  },
+  "hybrid_search": {
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+    "source_url": "https://myscale.com/docs/en/hybrid-search/",
+    "comment": "Hybrid Search"
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "https://myscale.com/docs/en/advanced-applications/object-detect/",
+    "comment": "via https://myscale.com/docs/en/advanced-applications/object-detect/#grouping-subqueries"
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "https://myscale.com/docs/en/functions/geo-functions/",
+    "comment": "via https://myscale.com/docs/en/functions/geospatial-functions/"
+  },
+  "multi_vec": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "MyScale Pricing",
+    "source_url": "https://myscale.com/pricing/",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://myscale.com/blog/myscale-on-aws/",
+    "comment": "via https://myscale.com/blog/myscale-on-aws/ > MyScale\u2019s MSTG algorithm allows vector data to be cached on local NVMe SSD disks, providing users with high-performance vector searches while significantly saving on memory usage."
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/neo4j.json b/docs/tools/vdb_table/data/neo4j.json
new file mode 100644
index 000000000..d762286c5
--- /dev/null
+++ b/docs/tools/vdb_table/data/neo4j.json
@@ -0,0 +1,152 @@
+{
+  "name": "Neo4j",
+  "links": {
+    "docs": "https://neo4j.com/docs/cypher-manual/current/indexes-for-vector-search/",
+    "github": "https://github.com/neo4j",
+    "website": "https://neo4j.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/96",
+    "poc_github": "https://github.com/akollegger",
+    "slug": "neo4j"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      ""
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 0,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "full",
+    "source_url": "",
+    "comment": "Java apps only"
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/nucliadb.json b/docs/tools/vdb_table/data/nucliadb.json
new file mode 100644
index 000000000..f870f10a1
--- /dev/null
+++ b/docs/tools/vdb_table/data/nucliadb.json
@@ -0,0 +1,153 @@
+{
+  "name": "Nuclia DB",
+  "links": {
+    "docs": "https://docs.nuclia.dev/docs/",
+    "github": "https://github.com/nuclia/nucliadb",
+    "website": "https://nuclia.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/90",
+    "poc_github": "https://github.com/clayrisse",
+    "slug": "nucliadb"
+  },
+  "oss": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "AGPLv3",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "rust",
+      "python"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 497,
+  "vector_launch_year": 0,
+  "metadata_filter": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/opensearch.json b/docs/tools/vdb_table/data/opensearch.json
new file mode 100644
index 000000000..b719905ae
--- /dev/null
+++ b/docs/tools/vdb_table/data/opensearch.json
@@ -0,0 +1,152 @@
+{
+  "name": "OpenSearch",
+  "links": {
+    "docs": "https://opensearch.org/docs/latest/search-plugins/knn/index/",
+    "github": "https://github.com/opensearch-project/OpenSearch",
+    "website": "https://opensearch.org/platform/search/vector-database.html",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/77",
+    "poc_github": "https://github.com/dtaivpp",
+    "slug": "opensearch"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "java"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 7900,
+  "vector_launch_year": 2021,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": "Only linear combination"
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "https://opensearch.org/docs/latest/aggregations/metric/index/",
+    "comment": "https://opensearch.org/docs/latest/aggregations/metric/index/"
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "full",
+    "source_url": "https://opensearch.org/docs/latest/search-plugins/neural-sparse-search/",
+    "comment": "https://opensearch.org/docs/latest/search-plugins/neural-sparse-search/"
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "full",
+    "source_url": "https://opensearch.org/docs/2.11/ml-commons-plugin/custom-local-models/",
+    "comment": "https://opensearch.org/docs/2.11/ml-commons-plugin/custom-local-models/"
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 100000000,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 10000,
+    "unlimited": false,
+    "source_url": "https://opensearch.org/docs/2.0/search-plugins/knn/approximate-knn/",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/oramasearch.json b/docs/tools/vdb_table/data/oramasearch.json
new file mode 100644
index 000000000..c22ab01b4
--- /dev/null
+++ b/docs/tools/vdb_table/data/oramasearch.json
@@ -0,0 +1,152 @@
+{
+  "name": "OramaSearch",
+  "links": {
+    "docs": "https://docs.oramasearch.com/open-source/",
+    "github": "https://github.com/oramasearch/orama",
+    "website": "http://oramasearch.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/82",
+    "poc_github": "https://github.com/MicheleRiva",
+    "slug": "oramasearch"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "typescript"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 6700,
+  "vector_launch_year": 2022,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "free plan / $4.99 per month (pro)",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": "Cloud solution only"
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/pgvector.json b/docs/tools/vdb_table/data/pgvector.json
new file mode 100644
index 000000000..78b93fd72
--- /dev/null
+++ b/docs/tools/vdb_table/data/pgvector.json
@@ -0,0 +1,152 @@
+{
+  "name": "pgvector",
+  "links": {
+    "docs": "",
+    "github": "https://github.com/pgvector/pgvector",
+    "website": "https://github.com/pgvector/pgvector",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/69",
+    "poc_github": "https://github.com/jkatz",
+    "slug": "pgvector"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "PostgreSQL Licence https://opensource.org/license/postgresql/",
+    "source_url": "https://opensource.org/license/postgresql/",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "c"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 6900,
+  "vector_launch_year": 2021,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "https://github.com/pgvector/pgvector",
+    "comment": "https://github.com/pgvector/pgvector#hybrid-search"
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": "Postgis"
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "https://www.postgresql.org/docs/current/textsearch.html",
+    "comment": "https://www.postgresql.org/docs/current/textsearch.html via GIST"
+  },
+  "embeddings_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": "(supabase)"
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "none",
+    "source_url": "",
+    "comment": "While pgvector does not provide this natively, you can get this either from PostgreSQL functionality like \"postgres_fdw\" or from extensions. You can also choose to subdivide your index through partitioning."
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 2000,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/pinecone.json b/docs/tools/vdb_table/data/pinecone.json
new file mode 100644
index 000000000..bbe06aa39
--- /dev/null
+++ b/docs/tools/vdb_table/data/pinecone.json
@@ -0,0 +1,152 @@
+{
+  "name": "Pinecone",
+  "links": {
+    "docs": "https://docs.pinecone.io/",
+    "github": "https://github.com/pinecone-io",
+    "website": "https://www.pinecone.io/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/65",
+    "poc_github": "https://github.com/jamescalam",
+    "slug": "pinecone"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Proprietary",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "rust"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 2019,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": "via namespaces"
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 40000,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 20000,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/qdrant.json b/docs/tools/vdb_table/data/qdrant.json
new file mode 100644
index 000000000..b221dfe92
--- /dev/null
+++ b/docs/tools/vdb_table/data/qdrant.json
@@ -0,0 +1,152 @@
+{
+  "name": "Qdrant",
+  "links": {
+    "docs": "https://qdrant.tech/documentation/",
+    "github": "https://github.com/qdrant/qdrant",
+    "website": "https://qdrant.tech/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/66",
+    "poc_github": "https://github.com/atarora",
+    "slug": "qdrant"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "rust"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 14700,
+  "vector_launch_year": 2021,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "https://qdrant.tech/articles/sparse-vectors/",
+    "comment": "https://qdrant.tech/articles/sparse-vectors/#hybrid-search-combining-sparse-and-dense-vectors"
+  },
+  "facets": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "full",
+    "source_url": "https://qdrant.tech/articles/sparse-vectors",
+    "comment": "https://qdrant.tech/articles/sparse-vectors"
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "https://qdrant.tech/documentation/concepts/indexing/",
+    "comment": "https://qdrant.tech/documentation/concepts/indexing/#full-text-index"
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "https://qdrant.github.io/fastembed/examples/Supported_Models/",
+    "comment": "via FastEmbed (Supported models: https://qdrant.github.io/fastembed/examples/Supported_Models/)"
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": "via collections/metadata"
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://qdrant.tech/documentation/concepts/storage/",
+    "comment": "https://qdrant.tech/documentation/concepts/storage/#configuring-memmap-storage"
+  },
+  "ephemeral": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "https://qdrant.tech/documentation/guides/distributed_deployment/",
+    "comment": "https://qdrant.tech/documentation/guides/distributed_deployment/#user-defined-sharding"
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/redis.json b/docs/tools/vdb_table/data/redis.json
new file mode 100644
index 000000000..d7d2cf9c3
--- /dev/null
+++ b/docs/tools/vdb_table/data/redis.json
@@ -0,0 +1,152 @@
+{
+  "name": "Redis Search",
+  "links": {
+    "docs": "https://redis.io/docs/get-started/vector-database/",
+    "github": "https://github.com/RedisAI/VectorSimilarity",
+    "website": "https://redis.com/solutions/use-cases/vector-database/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/81",
+    "poc_github": "https://github.com/tylerhutcherson",
+    "slug": "redis"
+  },
+  "oss": {
+    "support": "partial",
+    "source_url": "https://blog.opensource.org/the-sspl-is-not-an-open-source-license/",
+    "comment": "vector search component is under SSPL which is not fully OSS"
+  },
+  "license": {
+    "value": "(i) Redis Source Available License 2.0 (RSALv2) or (ii) the Server Side Public License v1 (SSPLv1)",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "c"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 62400,
+  "vector_launch_year": 2021,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "https://redis.io/docs/interact/search-and-query/advanced-concepts/vectors/",
+    "comment": "https://redis.io/docs/interact/search-and-query/advanced-concepts/vectors/#storing-vectors-in-json"
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "https://redis.io/docs/interact/search-and-query/advanced-concepts/scoring/",
+    "comment": "https://redis.io/docs/interact/search-and-query/advanced-concepts/scoring/"
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "https://redis.io/docs/interact/search-and-query/query/full-text/",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "none",
+    "source_url": "https://github.com/RedisVentures/redisvl",
+    "comment": "Embedding generation support available via client like https://github.com/RedisVentures/redisvl"
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "https://redis.com/blog/multi-tenancy-redis-enterprise/",
+    "comment": "https://redis.com/blog/multi-tenancy-redis-enterprise/"
+  },
+  "disk_index": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/requirements.txt b/docs/tools/vdb_table/data/requirements.txt
deleted file mode 100644
index 5cae28e80..000000000
--- a/docs/tools/vdb_table/data/requirements.txt
+++ /dev/null
@@ -1,5 +0,0 @@
-attrs==23.1.0
-jsonschema==4.20.0
-jsonschema-specifications==2023.11.2
-referencing==0.32.0
-rpds-py==0.13.2
diff --git a/docs/tools/vdb_table/data/rockset.json b/docs/tools/vdb_table/data/rockset.json
new file mode 100644
index 000000000..5343a91fc
--- /dev/null
+++ b/docs/tools/vdb_table/data/rockset.json
@@ -0,0 +1,152 @@
+{
+  "name": "Rockset",
+  "links": {
+    "docs": "https://docs.rockset.com/documentation/docs/vector-search",
+    "github": "https://github.com/rockset",
+    "website": "https://rockset.com/vector-search/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/102",
+    "poc_github": "https://github.com/brencon",
+    "slug": "rockset"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      ""
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 0,
+  "metadata_filter": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/turbopuffer.json b/docs/tools/vdb_table/data/turbopuffer.json
new file mode 100644
index 000000000..e90a7a239
--- /dev/null
+++ b/docs/tools/vdb_table/data/turbopuffer.json
@@ -0,0 +1,152 @@
+{
+  "name": "Turbopuffer",
+  "links": {
+    "docs": "https://turbopuffer.com/docs",
+    "github": "https://github.com/sirupsen",
+    "website": "http://turbopuffer.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/92",
+    "poc_github": "https://github.com/sirupsen",
+    "slug": "turbopuffer"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Proprietary",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "rust"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 0,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
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diff --git a/docs/tools/vdb_table/data/txtai.json b/docs/tools/vdb_table/data/txtai.json
new file mode 100644
index 000000000..1bb927789
--- /dev/null
+++ b/docs/tools/vdb_table/data/txtai.json
@@ -0,0 +1,152 @@
+{
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+  "multi_vec": {
+    "support": "full",
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+    "comment": "https://neuml.hashnode.dev/whats-new-in-txtai-60#heading-subindexes"
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diff --git a/docs/tools/vdb_table/data/typesense.json b/docs/tools/vdb_table/data/typesense.json
new file mode 100644
index 000000000..19ce3764a
--- /dev/null
+++ b/docs/tools/vdb_table/data/typesense.json
@@ -0,0 +1,152 @@
+{
+  "name": "Typesense",
+  "links": {
+    "docs": "https://typesense.org/docs/",
+    "github": "https://github.com/typesense/typesense",
+    "website": "https://typesense.org/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/94",
+    "poc_github": "https://github.com/jasonbosco",
+    "slug": "typesense"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "GPL-3.0",
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+    "comment": ""
+  },
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+      "c++"
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+    "comment": ""
+  },
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+  },
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+  "full_text": {
+    "support": "full",
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+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "https://typesense.org/docs/0.25.1/api/vector-search.html",
+    "comment": "https://typesense.org/docs/0.25.1/api/vector-search.html#creating-an-auto-embedding-field"
+  },
+  "embeddings_image": {
+    "support": "full",
+    "source_url": "https://typesense.org/docs/0.25.1/api/vector-search.html",
+    "comment": "https://typesense.org/docs/0.25.1/api/vector-search.html#use-cases:~:text=E%2D5-,CLIP,-OpenAI%27s%20Text%20Embeddings"
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\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/usearch.json b/docs/tools/vdb_table/data/usearch.json
new file mode 100644
index 000000000..e4706d2bd
--- /dev/null
+++ b/docs/tools/vdb_table/data/usearch.json
@@ -0,0 +1,152 @@
+{
+  "name": "USearch",
+  "links": {
+    "docs": "https://unum-cloud.github.io/usearch/",
+    "github": "https://github.com/unum-cloud/usearch",
+    "website": "https://unum-cloud.github.io/usearch/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/91",
+    "poc_github": "https://github.com/ashvardanian",
+    "slug": "usearch"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "c++"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 1061,
+  "vector_launch_year": 2023,
+  "metadata_filter": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "https://unum-cloud.github.io/usearch/python/reference.html",
+    "comment": "using the multi param in index creation"
+  },
+  "sparse_vectors": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
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+  "full_text": {
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+    "source_url": "",
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+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/vald.json b/docs/tools/vdb_table/data/vald.json
new file mode 100644
index 000000000..3752d0edc
--- /dev/null
+++ b/docs/tools/vdb_table/data/vald.json
@@ -0,0 +1,152 @@
+{
+  "name": "Vald",
+  "links": {
+    "docs": "https://vald.vdaas.org/docs/",
+    "github": "https://github.com/vdaas/vald",
+    "website": "http://github.com/vdaas/vald",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/80",
+    "poc_github": "https://github.com/kpango",
+    "slug": "vald"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "go"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 1400,
+  "vector_launch_year": 2021,
+  "metadata_filter": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
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+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
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+    "comment": ""
+  },
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+    "support": "none",
+    "source_url": "",
+    "comment": ""
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+    "comment": ""
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+  "in_process": {
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+    "comment": ""
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+    "comment": ""
+  },
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+    "comment": ""
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+    "comment": ""
+  },
+  "sharding": {
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+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": false,
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+    "comment": ""
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+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/validate.py b/docs/tools/vdb_table/data/validate.py
deleted file mode 100644
index 4ae2b295a..000000000
--- a/docs/tools/vdb_table/data/validate.py
+++ /dev/null
@@ -1,8 +0,0 @@
-from jsonschema import validate
-import json
-
-schema_obj = json.load(open("vendor.json.schema", "r"))
-vendor_obj = json.load(open("vendorX.json", "r"))
-
-validate(instance=vendor_obj, schema=schema_obj)
-
diff --git a/docs/tools/vdb_table/data/vectara.json b/docs/tools/vdb_table/data/vectara.json
new file mode 100644
index 000000000..ceade6eed
--- /dev/null
+++ b/docs/tools/vdb_table/data/vectara.json
@@ -0,0 +1,152 @@
+{
+  "name": "Vectara",
+  "links": {
+    "docs": "https://docs.vectara.com/docs/",
+    "github": "https://github.com/vectara",
+    "website": "http://vectara.com/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/74",
+    "poc_github": "https://github.com/ofermend",
+    "slug": "vectara"
+  },
+  "oss": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Proprietary",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "not known"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 0,
+  "vector_launch_year": 2021,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": "Only Linear combination"
+  },
+  "facets": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "none",
+    "source_url": "https://vectara.com/how-boomerang-takes-retrieval-augmented-generation-to-the-next-level-via-grounded-generation",
+    "comment": "[Note Vectara has its own embedding model called \"Boomerang\" that is SOTA (see https://vectara.com/how-boomerang-takes-retrieval-augmented-generation-to-the-next-level-via-grounded-generation/) and also works better than OpenAI or Cohere in terms of cross-lingual support (https://vectara.com/introducing-boomerang-vectaras-new-and-improved-retrieval-model-2/)]"
+  },
+  "embeddings_image": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "Pricing - Vectara",
+    "source_url": "https://vectara.com/pricing/",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": "via corpora or metadata"
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 50000000,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/vendor.schema.json b/docs/tools/vdb_table/data/vendor.schema.json
deleted file mode 100644
index d09bbf791..000000000
--- a/docs/tools/vdb_table/data/vendor.schema.json
+++ /dev/null
@@ -1,66 +0,0 @@
-{
-  "$schema": "https://json-schema.org/draft/2020-12/schema",
-  "$id": "vdb_table/schema/vendor",
-  "type": "object",
-
-  "properties": {
-    "name": { "type": "string" },
-    "website_url": { "type": "string" },
-    "docs_url": { "type": "string" },
-    "logo_url": { "type": "string" },
-    "point_of_contact_email": { "type": "string", "format": "email" },
-
-    "oss": { "allOf": [{"$ref": "#/$defs/feature"}], "$comment": "Open source & free to self-host" },
-    "managed_cloud": { "allOf": [{"$ref": "#/$defs/feature"}], "$comment": "Managed Cloud Offering" },
-    "disk_index": { "allOf": [{"$ref": "#/$defs/feature"}], "$comment": "Disk-based Index" },
-
-    "doc_size_limit": { "allOf": [{"$ref": "#/$defs/integerWithUnits"}], "$comment": "Metadata/Doc size limit" },
-    "vector_dimensions_max": { "allOf": [{"$ref": "#/$defs/integer"}], "$comment": "Maximum integer of vector dimensions" },
-
-    "license": { "allOf": [{"$ref": "#/$defs/string"}], "$comment": "OSS license for the core product" }
-  },
-
-  "$defs": {
-    "feature": {
-      "$id": "feature",
-      "type": "object",
-      "properties": {
-        "support": { "enum": ["none", "partial", "full"]},
-        "source_level": {"enum": ["", "claimed", "documented"]},
-        "source_url": {"type": "string"},
-        "comment": {"type": "string"}
-      }
-    },
-    "string": {
-      "$id": "string",
-      "type": "object",
-      "properties": {
-        "value": {"type": "string"},
-        "source_level": {"enum": ["", "claimed", "documented"]},
-        "source_url": {"type": "string"},
-        "comment": {"type": "string"}
-      }
-    },
-    "integer": {
-      "$id": "integer",
-      "type": "object",
-      "properties": {
-        "value": {"type": "integer"},
-        "source_level": {"enum": ["", "claimed", "documented"]},
-        "source_url": {"type": "string"},
-        "comment": {"type":"string"}
-      }
-    },
-    "integerWithUnits": {
-      "$id": "integerWithUnits",
-      "type": "object",
-      "properties": {
-        "value": {"type": "integer"},
-        "unit": {"type": "string"},
-        "source_level": {"enum": ["", "claimed", "documented"]},
-        "source_url": {"type": "string"},
-        "comment": {"type": "string"}
-      }
-    }
-  }
-}
diff --git a/docs/tools/vdb_table/data/vendorX.json b/docs/tools/vdb_table/data/vendorX.json
deleted file mode 100644
index f32e06e25..000000000
--- a/docs/tools/vdb_table/data/vendorX.json
+++ /dev/null
@@ -1,38 +0,0 @@
-{
-  "name": "vendorX",
-  "website_url": "https://vendorX.com",
-  "docs_url": "https://docs.vendorX.com",
-  "logo_url": "https://images.vendorX.com/logo.png",
-  "point_of_contact_email": "poc@vendorx.com",
-  "oss": {
-    "support": "full",
-    "source_level": "documented",
-    "source_url": "https://github.com/vendorx/vendorx/license.md"
-  },
-  "managed_cloud": {
-    "support": "none"
-  },
-  "disk_index": {
-    "support": "partial",
-    "source_level": "claimed",
-    "source_url": "",
-    "comment": "We support disk indices, but we do it under the hood to save cost and have no way to prove that to you."
-  },
-  "doc_size_limit": {
-    "value": 50,
-    "unit": "MB",
-    "source_level": "documented",
-    "source_url": "https://docs.vendorX.com/limits.html"
-  },
-  "vector_dimensions_max": {
-    "value": 10000,
-    "source_level": "documented",
-    "source_url": "https://docs.vendorX.com/limits.html",
-    "comment": "Can be configured to be more, but we don't have the docs for how to do that yet"
-  },
-  "license": {
-    "value": "Apache-2.0",
-    "source_level": "documented",
-    "source_url": "https://github.com/vendorx/vendorx/license.md"
-  }
-}
diff --git a/docs/tools/vdb_table/data/vespa.json b/docs/tools/vdb_table/data/vespa.json
new file mode 100644
index 000000000..44ab68370
--- /dev/null
+++ b/docs/tools/vdb_table/data/vespa.json
@@ -0,0 +1,153 @@
+{
+  "name": "Vespa",
+  "links": {
+    "docs": "https://docs.vespa.ai/",
+    "github": "https://github.com/vespa-engine/vespa",
+    "website": "https://vespa.ai/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/70",
+    "poc_github": "https://github.com/oyving",
+    "slug": "vespa"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "Apache-2.0",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "java",
+      "c++"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 5000,
+  "vector_launch_year": 2017,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "https://cloud.vespa.ai/price-calculator",
+    "source_url": "https://cloud.vespa.ai/price-calculator",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_tenancy": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://docs.vespa.ai/en/proton.html",
+    "comment": "https://docs.vespa.ai/en/proton.html#index"
+  },
+  "ephemeral": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/data/weaviate.json b/docs/tools/vdb_table/data/weaviate.json
new file mode 100644
index 000000000..e1dec633f
--- /dev/null
+++ b/docs/tools/vdb_table/data/weaviate.json
@@ -0,0 +1,152 @@
+{
+  "name": "Weaviate",
+  "links": {
+    "docs": "https://weaviate.io/developers/weaviate",
+    "github": "https://github.com/weaviate/weaviate",
+    "website": "http://weaviate.io/",
+    "vendor_discussion": "https://github.com/superlinked/VectorHub/discussions/67",
+    "poc_github": "https://github.com/StefanBogdan",
+    "slug": "weaviate"
+  },
+  "oss": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "license": {
+    "value": "BSD",
+    "source_url": "",
+    "comment": ""
+  },
+  "dev_languages": {
+    "value": [
+      "go"
+    ],
+    "source_url": "",
+    "comment": ""
+  },
+  "github_stars": 8300,
+  "vector_launch_year": 2019,
+  "metadata_filter": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "hybrid_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": "RRF*+RSF*"
+  },
+  "facets": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "geo_search": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "multi_vec": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "sparse_vectors": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "bm25": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "full_text": {
+    "support": "full",
+    "source_url": "https://weaviate.io/developers/weaviate/concepts/indexing",
+    "comment": "https://weaviate.io/developers/weaviate/concepts/indexing#introduction"
+  },
+  "embeddings_text": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_image": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "embeddings_structured": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "rag": {
+    "support": "full",
+    "source_url": "https://weaviate.io/developers/weaviate/modules/reader-generator-modules/generative-openai",
+    "comment": "Generative Search - OpenAI | Weaviate - vector databaseweaviate/modules/reader-generator-modules/generative-openai"
+  },
+  "recsys": {
+    "support": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "langchain": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "llamaindex": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "managed_cloud": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "pricing": {
+    "value": "",
+    "source_url": "",
+    "comment": ""
+  },
+  "in_process": {
+    "support": "full",
+    "source_url": "https://weaviate.io/developers/weaviate/installation/embedded",
+    "comment": "https://weaviate.io/developers/weaviate/installation/embedded"
+  },
+  "multi_tenancy": {
+    "support": "full",
+    "source_url": "",
+    "comment": ""
+  },
+  "disk_index": {
+    "support": "full",
+    "source_url": "https://weaviate.io/developers/weaviate/concepts/vector-index",
+    "comment": "https://weaviate.io/developers/weaviate/concepts/vector-index#flat-index"
+  },
+  "ephemeral": {
+    "support": "none",
+    "source_url": "",
+    "comment": ""
+  },
+  "sharding": {
+    "support": "full",
+    "source_url": "https://weaviate.io/developers/weaviate/concepts/cluster",
+    "comment": "https://weaviate.io/developers/weaviate/concepts/cluster https://weaviate.io/developers/weaviate/concepts/replication-architecture"
+  },
+  "doc_size": {
+    "bytes": 0,
+    "unlimited": true,
+    "source_url": "",
+    "comment": ""
+  },
+  "vector_dims": {
+    "value": 65535,
+    "unlimited": false,
+    "source_url": "",
+    "comment": ""
+  }
+}
\ No newline at end of file
diff --git a/docs/tools/vdb_table/dataTypeMapping.txt b/docs/tools/vdb_table/dataTypeMapping.txt
deleted file mode 100644
index e94650194..000000000
--- a/docs/tools/vdb_table/dataTypeMapping.txt
+++ /dev/null
@@ -1,38 +0,0 @@
-Rich text - Open-source & free to self-host	
-Rich text - Managed Cloud Offering	
-Rich text - Disk-based Index	
-Rich text - Multi-tenancy Support	
-Rich text - In-built Text Embeddings creation(Bring-your-own-model)	
-Rich text - In-built Image Embedding creation	
-Rich text - Metadata Filtering	
-Rich text - Embeddable	
-Rich text - Multiple vectors per point	
-Rich text - Langchain integration	
-Rich text - Llama index integration	
-Rich text - Hybrid Search	
-Rich text - BM25 support	
-Rich text - Sparse Vectors Support	
-Rich text - Full-text Search Engine	
-Rich text - Facets (Aggregations with Count)	
-Rich text - GeoSearch Support	
-Multiple select - Metadata/Doc size limit	
-Single select - Max Dimensions	
-Rich text - Ephemeral Index support(without server)	
-Rich text - Sharding	
-Multiple select - License	
-Multiple select - Development Language	
-Number - Github Stars	
-Single select - First Release of Vector Search	
-Rich text - Pricing	
-Rich text - Calls LLM internally for RAG	
-Rich text - Recommendations API	
-Rich text - Personalization	
-Rich text - User events (clickstream)
-
-
-Inputs required
-
-Rich text = string
-Single select = string (string should be one of the already created ones, otherwise it'll create a new option)
-Multiple select = list of strings (string should be one of the already created ones, otherwise it'll create a new option)
-Number = integer
diff --git a/docs/tools/vdb_table/data_utils.py b/docs/tools/vdb_table/data_utils.py
new file mode 100644
index 000000000..2d9852bac
--- /dev/null
+++ b/docs/tools/vdb_table/data_utils.py
@@ -0,0 +1,267 @@
+import os
+import json
+import argparse
+import openpyxl
+import re
+import humanfriendly
+import glob
+from jsonschema import validate
+from url_normalize import url_normalize
+from collections import OrderedDict
+
+class JsonProp():
+    def __init__(self, prop) -> None:
+        self.prop = prop
+    
+    def id(self):
+        return self.prop[0]
+    
+    def type(self):
+        # Parse the type - either just {type: value} or the $ref thing from jsonschema
+        if 'type' in self.prop[1]:
+            return self.prop[1]['type']
+        return self.prop[1].get('allOf')[0]['$ref'].removeprefix('#/$defs/')
+    
+    def group(self):
+        # $comment is a reserved prop in jsonschema, we use it for display name and comment with | as separator
+        return self.prop[1].get('$comment','').split('|')[0].strip()
+    
+    def name(self):
+        # $comment is a reserved prop in jsonschema, we use it for display name and comment with | as separator
+        return self.prop[1].get('$comment','').split('|')[1].strip()
+    
+    def comment(self):
+        # $comment is a reserved prop in jsonschema, we use it for display name and comment with | as separator
+        name_and_comment = self.prop[1].get('$comment','').split('|')
+        if len(name_and_comment) > 1:
+            return name_and_comment[2].strip()
+        return ''
+
+    def __str__(self):
+        return "%s, %s, %s, %s, %s"%(self.id(), self.type(), self.group(), self.name(), self.comment())
+
+class JsonSchemaWrapper(): # Switch to XLSX
+    def __init__(self, schema) -> None:
+        self.schema = schema
+
+    def props(self):
+        return [JsonProp(prop) for prop in self.schema['properties'].items()]
+    
+    def prop_by_id(self, id):
+        for prop in self.props():
+            if prop.id() == id:
+                return prop
+        return None
+
+class JsonValueFactory():    
+    def backfillLinkFromValue(value, hyperlink):
+        URL_REGEX = r"\b((?:https?://)?(?:(?:www\.)?(?:[\da-z\.-]+)\.(?:[a-z]{2,6})|(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)|(?:(?:[0-9a-fA-F]{1,4}:){7,7}[0-9a-fA-F]{1,4}|(?:[0-9a-fA-F]{1,4}:){1,7}:|(?:[0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|(?:[0-9a-fA-F]{1,4}:){1,5}(?::[0-9a-fA-F]{1,4}){1,2}|(?:[0-9a-fA-F]{1,4}:){1,4}(?::[0-9a-fA-F]{1,4}){1,3}|(?:[0-9a-fA-F]{1,4}:){1,3}(?::[0-9a-fA-F]{1,4}){1,4}|(?:[0-9a-fA-F]{1,4}:){1,2}(?::[0-9a-fA-F]{1,4}){1,5}|[0-9a-fA-F]{1,4}:(?:(?::[0-9a-fA-F]{1,4}){1,6})|:(?:(?::[0-9a-fA-F]{1,4}){1,7}|:)|fe80:(?::[0-9a-fA-F]{0,4}){0,4}%[0-9a-zA-Z]{1,}|::(?:ffff(?::0{1,4}){0,1}:){0,1}(?:(?:25[0-5]|(?:2[0-4]|1{0,1}[0-9]){0,1}[0-9])\.){3,3}(?:25[0-5]|(?:2[0-4]|1{0,1}[0-9]){0,1}[0-9])|(?:[0-9a-fA-F]{1,4}:){1,4}:(?:(?:25[0-5]|(?:2[0-4]|1{0,1}[0-9]){0,1}[0-9])\.){3,3}(?:25[0-5]|(?:2[0-4]|1{0,1}[0-9]){0,1}[0-9])))(?::[0-9]{1,4}|[1-5][0-9]{4}|6[0-4][0-9]{3}|65[0-4][0-9]{2}|655[0-2][0-9]|6553[0-5])?(?:/[\w\.-]*)*/?)\b"
+        if hyperlink:
+            return hyperlink
+        parsed_url = re.search(URL_REGEX, value)
+        return parsed_url.group() if parsed_url else ""
+                
+    def convertValueToJson(schema, value, hyperlink):
+        return getattr(JsonValueFactory, schema.type())(value, hyperlink)
+    
+    def bytesWithSource(value, hyperlink):
+        try:
+            num_bytes = humanfriendly.parse_size(value)
+        except:
+            num_bytes = 0
+        return  {
+            "bytes": num_bytes,
+            "unlimited": True if "unlimited" in value.lower() else False,
+            "source_url": hyperlink,
+            "comment": ""
+        }
+
+    def featureWithSource(value, hyperlink):
+        support = ""
+        if "✅" in value: support = "full"
+        if "🟨" in value: support = "partial"
+        if "❌" in value: support = "none"
+        return {
+            "support": support,
+            "source_url": JsonValueFactory.backfillLinkFromValue(value, hyperlink),
+            "comment": "" if not value else value.translate({ord(x): '' for x in ["✅","❌","🟨"]}).strip()
+        }
+
+    def integer(value, _hyperlink):
+        try:
+            return int(value)
+        except:
+            return 0
+
+    def integerWithSource(value, hyperlink):
+        try:
+            integer = int(value)
+        except:
+            integer = 0
+        return {    
+            "value": integer,
+            "unlimited": True if "unlimited" in value.lower() else False,
+            "source_url": hyperlink,
+            "comment": ""
+        }
+
+    def links(value, _hyperlink):
+        link_list = value.split("|")
+        return {
+            "docs": url_normalize(link_list[0]),
+            "github": url_normalize(link_list[1]),
+            "website": url_normalize(link_list[2]),
+            "vendor_discussion": url_normalize(link_list[3]),
+            "poc_github": url_normalize("https://github.com/%s"%(link_list[4])),
+            "slug": link_list[5]
+        }
+
+    def string(value, _hyperlink):
+        return value
+
+    def stringListWithSource(value, hyperlink):
+        return {
+            "value": [val.strip().lower() for val in value.split(",")],
+            "source_url": hyperlink,
+            "comment": ""
+        }
+
+    def stringWithSource(value, hyperlink):
+        return {    
+            "value": value,
+            "source_url": JsonValueFactory.backfillLinkFromValue(value, hyperlink),
+            "comment": ""
+        }
+    
+class XLSXWrapper():
+    # Preparation steps for the raw CSV that have to be done manually:
+    # 1. Fill in missing headers based on the vendor.schema.json file. Currently there are 2:
+    #    Links
+    #    In-built Structured Data Embedding creation
+    # 2. Replace new-line characters in the file with spaces to make sure you have a valid CSV.
+    HEADER_TO_SCHEMA_ID = {
+        "DB | Attributes": "name",
+        "Links": "links",
+        "License": "license",
+        "Development Language": "dev_languages",
+        "Github Stars": "github_stars",
+        "First Release of Vector Search": "vector_launch_year",
+        "Metadata Filtering": "metadata_filter",
+        "Hybrid Search": "hybrid_search",
+        "Facets (Aggregations with Count)": "facets",
+        "GeoSearch Support": "geo_search",
+        "Multiple vectors per point": "multi_vec",
+        "Sparse Vectors Support": "sparse_vectors",
+        "BM25 support": "bm25",
+        "Full-text Search Engine": "full_text",
+        "In-built Text Embeddings creation (Bring-your-own-model)": "embeddings_text",
+        "In-built Image Embedding creation": "embeddings_image",
+        "In-built Structured Data Embedding creation": "embeddings_structured",
+        "Calls LLM internally for RAG": "rag",
+        "Recommendations API": "recsys",
+        "Langchain integration": "langchain",
+        "Llama index integration": "llamaindex",
+        "Open-source & free to self-host": "oss",
+        "Managed Cloud Offering": "managed_cloud",
+        "Pricing": "pricing",
+        "Embeddable": "in_process",
+        "Multi-tenancy Support": "multi_tenancy",
+        "Disk-based Index": "disk_index",
+        "Ephemeral Index support (without server)": "ephemeral",
+        "Sharding": "sharding",
+        "Metadata/Doc size limit": "doc_size",
+        "Max Dimensions": "vector_dims"
+    }
+
+    def map_header_to_schema_id(self, header):
+        return self.HEADER_TO_SCHEMA_ID.get(header.replace("\n",""), None)
+
+    def __init__(self, xlsx_path, xlsx_sheet, table_schema) -> None:
+        self.xlsx_path = xlsx_path
+        self.table_schema = table_schema
+        self.xlsx_sheet = xlsx_sheet
+    
+    def value_to_json(self, value, schema):
+        val = value.value
+        if not val:
+            val = None
+        elif isinstance(val, float):
+            val = str(int(val))
+        else:
+            val = str(val)
+
+        return JsonValueFactory.convertValueToJson(
+            schema, "" if not val else val,
+            "" if not value.hyperlink else value.hyperlink.target)
+
+    def row_to_json(self, header, row):
+        # Collect the properties from the row.
+        data = {}
+        for i, value in enumerate(row):
+            key = self.HEADER_TO_SCHEMA_ID.get(header[i].value, None)
+            if key: 
+                data[key] = self.value_to_json(value, self.table_schema.prop_by_id(key))
+        # Order the properties according to the schema.
+        result = OrderedDict()
+        for prop in self.table_schema.props():
+            result[prop.id()] = data[prop.id()]
+
+        return result
+    
+    def to_json(self, output_dir):
+        workbook = openpyxl.load_workbook(self.xlsx_path, data_only=True)
+        sheet = workbook[self.xlsx_sheet]
+        header_row = []
+        for i, row in enumerate(sheet.iter_rows()):
+            if not row[0].value: break
+            if i == 0:
+                header_row = row
+            else:
+                print("Processing", row[0].value)
+                output_obj = self.row_to_json(header_row, row)
+                with open(os.path.join(output_dir, output_obj["links"]["slug"]+".json"), "w") as output_file:
+                    json.dump(output_obj, output_file, indent=2)
+
+class CLI():
+    # Use XLSX instead of CSV to preserve the hyperlinks in the original data.
+    def xlsx_to_json(self, path_to_schema, output_dir, path_to_xlsx, xlsx_sheet):
+        table_schema = JsonSchemaWrapper(json.load(open(path_to_schema, "r")))
+        xlsx = XLSXWrapper(path_to_xlsx, xlsx_sheet, table_schema)
+        xlsx.to_json(output_dir)
+    
+    def json_to_bundle(self, data_glob):
+        obj_list = []
+        for name in glob.glob(data_glob):  
+            obj_list.append(json.load(open(name, "r"), object_pairs_hook=OrderedDict))
+        with open("bundle.json", "w") as output_file:
+            json.dump(obj_list, output_file, indent=2)
+    
+    def json_validate(self, path_to_schema, data_glob):
+        schema_obj = json.load(open(path_to_schema, "r"))
+        for name in glob.glob(data_glob):  
+            vendor_obj = json.load(open(name, "r"))
+            validate(instance=vendor_obj, schema=schema_obj)
+
+
+# Executes when your script is called from the command-line:
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description='CLI for managing the VDB json files in /data')
+    parser.add_argument('command', help='The command you want to perform: xlsx_to_json')
+    parser.add_argument('-sp','--schema_path', help='Path to the schema.json file.')
+    parser.add_argument('-xp','--xlsx_path', help='Path to the legacy XSLX file.')
+    parser.add_argument('-xs','--xlsx_sheet', help='Sheet to use in the XLSX file.')
+    parser.add_argument('-od','--output_dir', help='Output directory for the vendor JSONs.')
+    parser.add_argument('-dd','--data_glob', help='Glob pattern for the vendor JSON data.')
+
+    args = parser.parse_args()
+    
+    cli = CLI()
+    if args.command == 'xlsx_to_json':
+        cli.xlsx_to_json(args.schema_path, args.output_dir, args.xlsx_path, args.xlsx_sheet)
+
+    if args.command == 'json_to_bundle':
+        cli.json_to_bundle(args.data_glob)
+    
+    if args.command == 'json_validate':
+        cli.json_validate(args.schema_path, args.data_glob)
+
diff --git a/docs/tools/vdb_table/raw_data_dec31.xlsx b/docs/tools/vdb_table/raw_data_dec31.xlsx
new file mode 100644
index 000000000..0e65dfa70
Binary files /dev/null and b/docs/tools/vdb_table/raw_data_dec31.xlsx differ
diff --git a/docs/tools/vdb_table/raw_data_jan9.xlsx b/docs/tools/vdb_table/raw_data_jan9.xlsx
new file mode 100644
index 000000000..a5b20b324
Binary files /dev/null and b/docs/tools/vdb_table/raw_data_jan9.xlsx differ
diff --git a/docs/tools/vdb_table/requirements.txt b/docs/tools/vdb_table/requirements.txt
new file mode 100644
index 000000000..2fa2ee0af
--- /dev/null
+++ b/docs/tools/vdb_table/requirements.txt
@@ -0,0 +1,22 @@
+annotated-types==0.6.0
+attrs==23.1.0
+certifi==2023.11.17
+charset-normalizer==3.3.2
+et-xmlfile==1.1.0
+humanfriendly==10.0
+idna==3.6
+inflection==0.5.1
+jsonschema==4.20.0
+jsonschema-specifications==2023.11.2
+openpyxl==3.1.2
+pyairtable==2.2.1
+pydantic==2.5.2
+pydantic_core==2.14.5
+python-dotenv==1.0.0
+referencing==0.32.0
+requests==2.31.0
+rpds-py==0.13.2
+six==1.16.0
+typing_extensions==4.9.0
+url-normalize==1.4.3
+urllib3==2.1.0
diff --git a/docs/tools/vdb_table/updateAirtable.py b/docs/tools/vdb_table/updateAirtable.py
deleted file mode 100644
index ba2863ac9..000000000
--- a/docs/tools/vdb_table/updateAirtable.py
+++ /dev/null
@@ -1,121 +0,0 @@
-import os
-import requests
-from dotenv import load_dotenv
-import json
-from pyairtable import Api
-from pyairtable.orm import Model, fields as F
-
-load_dotenv()
-airtable_api_key = os.getenv("AIRTABLE_API_KEY")
-BASE_ID = os.getenv("BASE_ID")
-TABLE_ID = os.getenv("TABLE_ID")
-
-
-api = Api(airtable_api_key)
-base = api.base(BASE_ID)
-table = api.table(BASE_ID, TABLE_ID)
-# schema_obj = json.load(open("vendor.schema.json", "r"))
-
-
-#TODO
-def get_json_data():
-
-    return list_of_fields, records
-
-
-
-def update_table_fields():
-
-    #TODO
-    #code to check if there is a new field (column) added in the JSON, 
-    #if yes then create that field in the table
-
-    table_schema = table.schema()
-    return table_schema
-
-
-def update_table_records():
-
-    list_of_fields = ["Database Name",
-                      "Open-source & free to self-host", 
-                      "Managed Cloud Offering",
-                      "Disk-based Index",
-                      "Multi-tenancy Support",
-                      "In-built Text Embeddings creation(Bring-your-own-model)",
-                      "In-built Image Embedding creation",
-                      "Metadata Filtering",
-                      "Embeddable",
-                      "Multiple vectors per point",
-                      "Langchain integration",
-                      "Llama index integration",
-                      "Hybrid Search",
-                      "BM25 support",
-                      "Sparse Vectors Support",
-                      "Full-text Search Engine",
-                      "Facets (Aggregations with Count)",
-                      "GeoSearch Support",
-                      "Metadata/Doc size limit",
-                      "Max Dimensions",
-                      "Ephemeral Index support(without server)",
-                      "Sharding",
-                      "License",
-                      "Development Language",
-                      "Github Stars",
-                      "First Release of Vector Search",
-                      "Pricing",
-                      "Calls LLM internally for RAG",
-                      "Recommendations API",
-                      "Personalization",
-                      "User events (clickstream)"
-                    ]
-
-    class VDB(Model):
-        field_0 = F.TextField(list_of_fields[0])
-        field_1 = F.RichTextField(list_of_fields[1])
-        # field_2 = F.RichTextField(list_of_fields[2])
-        # field_3 = F.RichTextField(list_of_fields[3])
-        # field_4 = F.RichTextField(list_of_fields[4])
-        # field_5 = F.RichTextField(list_of_fields[5])
-        # field_6 = F.RichTextField(list_of_fields[6])
-        # field_7 = F.RichTextField(list_of_fields[7])
-        # field_8 = F.RichTextField(list_of_fields[8])
-        # field_9 = F.RichTextField(list_of_fields[9])
-        # field_10 = F.RichTextField(list_of_fields[10])
-        # field_11 = F.RichTextField(list_of_fields[11])
-        # field_12 = F.RichTextField(list_of_fields[12])
-        # field_13 = F.RichTextField(list_of_fields[13])
-        # field_14 = F.RichTextField(list_of_fields[14])
-        # field_15 = F.RichTextField(list_of_fields[15])
-        # field_16 = F.RichTextField(list_of_fields[16])
-        # field_17 = F.RichTextField(list_of_fields[17])
-        # field_18 = F.MultipleSelectField(list_of_fields[18])
-        # field_19 = F.SelectField(list_of_fields[19])
-        # field_20 = F.RichTextField(list_of_fields[20])
-        # field_21 = F.RichTextField(list_of_fields[21])
-        # field_22 = F.MultipleSelectField(list_of_fields[22])
-        # field_23 = F.MultipleSelectField(list_of_fields[23])
-        # field_24 = F.NumberField(list_of_fields[24])
-        # field_25 = F.SelectField(list_of_fields[25])
-        # field_26 = F.RichTextField(list_of_fields[26])
-        # field_27 = F.RichTextField(list_of_fields[27])
-        # field_28 = F.RichTextField(list_of_fields[28])
-        # field_29 = F.RichTextField(list_of_fields[29])
-        # field_30 = F.RichTextField(list_of_fields[30])
-
-        class Meta:
-            base_id = BASE_ID
-            table_name = TABLE_ID
-            api_key = airtable_api_key
-
-    database_instance = VDB(
-        field_0="Pinecone",
-        field_1="✅",
-    )
-
-    assert database_instance.save()
-    print(database_instance.exists())
-    print(database_instance.id)
-
-
-
-update_table_records()
\ No newline at end of file
diff --git a/docs/tools/vdb_table/vendor.schema.json b/docs/tools/vdb_table/vendor.schema.json
new file mode 100644
index 000000000..f05474fa8
--- /dev/null
+++ b/docs/tools/vdb_table/vendor.schema.json
@@ -0,0 +1,107 @@
+{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "$id": "vdb_table/schema/vendor",
+  "type": "object",
+
+  "properties": {
+    "name": {"type": "string", "$comment": "About | Vendor | " },
+    "links": {"allOf": [{"$ref": "#/$defs/links"}], "$comment": "About | Links | " },
+    "oss": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "About | OSS | The code-base is open source and users can self-host it for free." },
+    "license": {"allOf": [{"$ref": "#/$defs/stringWithSource"}], "$comment": "About | License | The license the source code is released under." },
+    "dev_languages": {"allOf": [{"$ref": "#/$defs/stringListWithSource"}], "$comment": "About | Dev Lang | The language the database is developed in." },
+    "github_stars": {"type": "integer", "$comment": "About | GitHub ⭐ | The number of stars for the core product repository." },
+    "vector_launch_year": {"type": "integer", "$comment": "About | VSS Launch | The year of the first release for the vector search functionality." },
+    "metadata_filter": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | Filters | Metadata filtering support within vector search - allowing users to refine results based on additional contextual informatio and enhancing precision in search queries. Not to be confused with filters/faceting in Lucene based keyword search." },
+    "hybrid_search": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | Hybrid Search | Built-in blending of the 2 lists (keyword & vector search results) being done natively within the DB using something like Reciprocal Rank Fusion." },
+    "facets": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | Facets | Built-in aggregations on facets and facet cardinality calculation (similar to Lucene)." },
+    "geo_search": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | Geo Search | Built-in geospatial index for location queries." },
+    "multi_vec": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | Multi-Vector | Ability to create and index multiple vectors for a given document." },
+    "sparse_vectors": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | Sparse | Bring your own sparse vectors (e.g. TF-IDF) and have them be indexed and available for retrieval in the database." },
+    "bm25": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | BM25 | Built-in tokenization, indexing, and scoring for BM25." },
+    "full_text": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Search | Full-Text | Built-in inverted index for terms, capable of boolean queries (similar to Lucene)." },
+    "embeddings_text": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Models | Text Model | Ability to plug in commonly-used embedding models for text vectorization (Sentence-transformers/HuggingFace feature extraction models)" },
+    "embeddings_image": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Models | Image Model | Ability to plug in image embedding models for vectorization (e.g. CLIP)." },
+    "embeddings_structured": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Models | Struct Model | Ability to plug in models used to embedd structured data like user clicks and graphs." },
+    "rag": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "APIs | RAG | Calls a LLM internally for a full-stack Retrieval Augmented Generation solution." },
+    "recsys": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "APIs | RecSys | Built-in support for recommendation system functionality, e.g. a solution that refines the results based on behavioral data." },
+    "langchain": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "APIs | LangChain | Built-in integration with the LlamaIndex library." },
+    "llamaindex": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "APIs | LlamaIndex | Built-in integration with the LangChain library." },
+    "managed_cloud": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Ops | Managed | A managed cloud offering is available." },
+    "pricing": {"allOf": [{"$ref": "#/$defs/stringWithSource"}], "$comment": "Ops | Pricing | The pricing models very widely, so this field is unstructured and ideally points to a pricing page." },
+    "in_process": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Ops | In-process | Ability to run embedded within the application process, which leads to a simpler deployment and management in situations when the whole workload fits into one machine." },
+    "multi_tenancy": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Ops | Multi-Tenant | Multi-tenancy - the ability to store multiple isolated indexes within one database instance." },
+    "disk_index": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Ops | Disk Index | Ability to store the vector index state on disk." },
+    "ephemeral": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Ops | Ephemeral Index | Ephemeral index support without a server." },
+    "sharding": {"allOf": [{"$ref": "#/$defs/featureWithSource"}], "$comment": "Ops | Sharding | The search index is sharded across multiple machines." },
+    "doc_size": {"allOf": [{"$ref": "#/$defs/bytesWithSource"}], "$comment": "Ops | Document Size | Maximum size of a stored document." },
+    "vector_dims": {"allOf": [{"$ref": "#/$defs/integerWithSource"}], "$comment": "Ops | Vector Dims | Maximum number of vector dimensions." }    
+  
+  },
+
+  "$defs": {
+    "links": {
+      "$id": "links",
+      "type": "object",
+      "properties": {
+        "docs": {"type": "string"},
+        "github": {"type": "string"},
+        "website": {"type": "string"},
+        "vendor_discussion": {"type": "string"},
+        "poc_github": {"type": "string"},
+        "slug": {"type": "string"}
+      }
+    },
+    "featureWithSource": {
+      "$id": "featureWithSource",
+      "type": "object",
+      "properties": {
+        "support": {"enum": ["", "none", "partial", "full"]},
+        "source_url": {"type": "string"},
+        "comment": {"type": "string"}
+      }
+    },
+    "stringWithSource": {
+      "$id": "stringWithSource",
+      "type": "object",
+      "properties": {
+        "value": {"type": "string"},
+        "source_url": {"type": "string"},
+        "comment": {"type": "string"}
+      }
+    },
+    "stringListWithSource": {
+      "$id": "stringListWithSource",
+      "type": "object",
+      "properties": {
+        "value": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          }
+        },
+        "source_url": {"type": "string"},
+        "comment": {"type": "string"}
+      }
+    },
+    "integerWithSource": {
+      "$id": "integerWithSource",
+      "type": "object",
+      "properties": {
+        "value": {"type": "integer"},
+        "unlimited": {"type": "boolean"},
+        "source_url": {"type": "string"},
+        "comment": {"type":"string"}
+      }
+    },
+    "bytesWithSource": {
+      "$id": "bytesWithSource",
+      "type": "object",
+      "properties": {
+        "bytes": {"type": "integer"},
+        "unlimited": {"type": "boolean"},
+        "source_url": {"type": "string"},
+        "comment": {"type":"string"}
+      }
+    }
+  }
+}