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+---
+title: MongoDB
+description: dlt verified source for MongoDB
+keywords: [mongodb, verified source, mongo database]
+---
+
+# MongoDB
+
+:::info Need help deploying these sources, or figuring out how to run them in your data stack?
+
+[Join our Slack community](https://dlthub-community.slack.com/join/shared_invite/zt-1slox199h-HAE7EQoXmstkP_bTqal65g)
+or [book a call](https://calendar.app.google/kiLhuMsWKpZUpfho6) with our support engineer Adrian.
+:::
+
+[MongoDB](https://www.mongodb.com/what-is-mongodb) is a NoSQL database that stores JSON-like
+documents.
+
+This MongoDB `dlt` verified source and
+[pipeline example](https://github.com/dlt-hub/verified-sources/blob/master/sources/mongodb_pipeline.py)
+loads data using “MongoDB" source to the destination of your choice.
+
+Sources and resources that can be loaded using this verified source are:
+
+| Name               | Description                                |
+|--------------------|--------------------------------------------|
+| mongodb            | loads a specific MongoDB database          |
+| mongodb_collection | loads a collection from a MongoDB database |
+
+## Setup Guide
+
+### Grab credentials
+
+#### Grab `connection_url`
+
+MongoDB can be configured in multiple ways. Typically, the connection URL format is:
+
+```text
+connection_url = "mongodb://dbuser:passwd@host.or.ip:27017"
+```
+
+For details on connecting to MongoDB and obtaining the connection URL, see
+[the documentation.](https://www.mongodb.com/docs/drivers/go/current/fundamentals/connection/)
+
+Here are the typical ways to configure MongoDB and their connection URLs:
+
+| Name                | Description                                                                           | Connection URL Example                            |
+|---------------------|---------------------------------------------------------------------------------------|---------------------------------------------------|
+| Local Installation  | Install on Windows, macOS, Linux using official packages.                             | "mongodb://dbuser:passwd@host.or.ip:27017"        |
+| Docker              | Deploy using the MongoDB Docker image.                                                | "mongodb://dbuser:passwd@docker.host:27017"       |
+| MongoDB Atlas       | MongoDB’s managed service on AWS, Azure, and Google Cloud.                            | "mongodb+srv://dbuser:passwd@cluster.mongodb.net" |
+| Managed Cloud       | AWS DocumentDB, Azure Cosmos DB, and others offer MongoDB as a managed database.      | "mongodb://dbuser:passwd@managed.cloud:27017"     |
+| Configuration Tools | Use Ansible, Chef, or Puppet for automation of setup and configuration.               | "mongodb://dbuser:passwd@config.tool:27017"       |
+| Replica Set         | Set up for high availability with data replication across multiple MongoDB instances. | "mongodb://dbuser:passwd@replica.set:27017"       |
+| Sharded Cluster     | Scalable distribution of datasets across multiple MongoDB instances.                  | "mongodb://dbuser:passwd@shard.cluster:27017"     |
+| Kubernetes          | Deploy on Kubernetes using Helm charts or operators.                                  | "mongodb://dbuser:passwd@k8s.cluster:27017"       |
+| Manual Tarball      | Install directly from the official MongoDB tarball, typically on Linux.               | "mongodb://dbuser:passwd@tarball.host:27017"      |
+
+> Note: The provided URLs are example formats; adjust as needed for your specific setup.
+
+#### Grab `database and collections`
+
+1. To grab "database and collections" you must have MongoDB shell installed. For installation 
+   guidance, refer to [documentation here.](https://www.mongodb.com/docs/mongodb-shell/install/)
+
+1. Modify the example URLs with your credentials (dbuser & passwd) and host details.
+
+1. Connect to MongoDB:
+
+   ```bash
+   mongo "mongodb://dbuser:passwd@your_host:27017"
+   ```
+
+1. List all Databases:
+
+   ```bash
+   show dbs
+   ```
+
+1. View Collections in a Database:
+
+   1. Switch to Database:
+      ```bash
+      use your_database_name
+      ```
+   1. Display its Collections:
+      ```bash
+      show collections
+      ```
+
+1. Disconnect:
+
+   ```bash
+   exit
+   ```
+
+>Note the database and collection names for future source configuration.
+
+### Prepare your data
+
+Data in MongoDB is stored in BSON (Binary JSON) format, which allows for embedded documents or
+nested data. It employs a flexible schema, and its key terms include:
+
+`Documents`: Key-value pairs representing data units.
+
+`Collections`: Groups of documents, similar to database tables but without a fixed schema.
+
+`Databases`: Containers for collections; a single MongoDB server can have multiple databases.
+
+The `dlt` converts nested data into relational tables, deduces data types, and defines parent-child
+relationships, creating an adaptive schema for future data adjustments.
+
+### Initialize the verified source
+
+To get started with your data pipeline, follow these steps:
+
+1. Enter the following command:
+
+   ```bash
+   dlt init mongodb duckdb
+   ```
+
+   [This command](../../reference/command-line-interface) will initialize
+   [the pipeline example](https://github.com/dlt-hub/verified-sources/blob/master/sources/mongodb_pipeline.py)
+   with MongoDB as the [source](../../general-usage/source) and [duckdb](../destinations/duckdb.md)
+   as the [destination](../destinations).
+
+1. If you'd like to use a different destination, simply replace `duckdb` with the name of your
+   preferred [destination](../destinations).
+
+1. After running this command, a new directory will be created with the necessary files and
+   configuration settings to get started.
+
+For more information, read the
+[Walkthrough: Add a verified source.](../../walkthroughs/add-a-verified-source)
+
+### Add credentials
+
+1. Inside the `.dlt` folder, you'll find a file called `secrets.toml`, which is where you can
+   securely store your access tokens and other sensitive information. It's important to handle this
+   file with care and keep it safe. Here's what the file looks like:
+
+   ```toml
+   # put your secret values and credentials here
+   # do not share this file and do not push it to github
+   [sources.mongodb]
+   connection_url = "mongodb connection_url" # please set me up!
+   ```
+
+1. Replace the connection_url value with the [previously copied one](#grab-connection_url) to ensure
+   secure access to your MongoDB sources.
+
+1. Next, Follow the [destination documentation](../../dlt-ecosystem/destinations) instructions to
+   add credentials for your chosen destination, ensuring proper routing of your data to the final
+   destination.
+
+1. Next, store your configuration details in the `.dlt/config.toml`.
+
+   Here's what the `config.toml` looks like:
+
+   ```toml
+   [your_pipeline_name]  # Set your pipeline name here!
+   database = "defaultDB"  # Database name (Optional), default database is loaded if not provided.
+   collection_names = ["collection_1", "collection_2"] # Collection names (Optional), all collections are loaded if not provided.
+   ```
+
+   > Optionally, you can set database and collection names in ".dlt/secrets.toml" under
+   > [sources.mongodb] without listing the pipeline name.
+
+1. Replace the value of the "database" and "collections_names" with the ones
+   [copied above](#grab-database-and-collections).
+
+## Run the pipeline
+
+1. Before running the pipeline, ensure that you have installed all the necessary dependencies by
+   running the command:
+   ```bash
+   pip install -r requirements.txt
+   ```
+1. You're now ready to run the pipeline! To get started, run the following command:
+   ```bash
+   python3 mongodb_pipeline.py
+   ```
+1. Once the pipeline has finished running, you can verify that everything loaded correctly by using
+   the following command:
+   ```bash
+   dlt pipeline <pipeline_name> show
+   ```
+   For example, the `pipeline_name` for the above pipeline example is `local_mongo`, you may also
+   use any custom name instead.
+
+For more information, read the [Walkthrough: Run a pipeline.](../../walkthroughs/run-a-pipeline)
+
+## Sources and resources
+
+`dlt` works on the principle of [sources](../../general-usage/source) and
+[resources](../../general-usage/resource).
+
+### Source `mongodb`
+
+This function loads data from a MongoDB database, yielding one or multiple collections to be retrieved.
+
+```python
+@dlt.source
+def mongodb(
+    connection_url: str = dlt.secrets.value,
+    database: Optional[str] = dlt.config.value,
+    collection_names: Optional[List[str]] = dlt.config.value,
+    incremental: Optional[dlt.sources.incremental] = None,  # type: ignore[type-arg]
+    write_disposition: Optional[str] = dlt.config.value,
+) -> Iterable[DltResource]:
+```
+
+`connection_url`: MongoDB connection URL.
+
+`database`: Database name (defaults if unspecified).
+
+`collection_names`: Names of desired collections; loads all if not specified.
+
+`incremental`: Option for incremental data loading.
+
+`write_disposition`: Writing mode: "replace", "append", or "merge".
+
+
+### Source `mongo_collection`
+
+This function fetches a single collection from a MongoDB database using PyMongo.
+
+```python
+def mongodb_collection(
+    connection_url: str = dlt.secrets.value,
+    database: Optional[str] = dlt.config.value,
+    collection: str = dlt.config.value,
+    incremental: Optional[dlt.sources.incremental] = None,  # type: ignore[type-arg]
+    write_disposition: Optional[str] = dlt.config.value,
+) -> Any:
+```
+
+`collection`: Name of the collection to load.
+
+### Create your own pipeline
+
+If you wish to create your own pipelines, you can leverage source and resource methods from this
+verified source.
+
+1. Configure the pipeline by specifying the pipeline name, destination, and dataset as follows:
+
+   ```python
+   pipeline = dlt.pipeline(
+        pipeline_name="mongodb_pipeline",  # Use a custom name if desired
+        destination="duckdb",  # Choose the appropriate destination (e.g., duckdb, redshift, post)
+        dataset_name="mongodb_data"  # Use a custom name if desired
+   )
+   ```
+
+1. To load all the collections in a database:
+
+   ```python
+   load_data = mongodb()
+   load_info = pipeline.run(load_data, write_disposition="replace")
+   print(load_info)
+   ```
+
+1. To load a specific collections from the database:
+
+   ```python
+   load_data = mongodb().with_resources("collection_1", "collection_2")
+   load_info = pipeline.run(load_data, write_disposition="replace")
+   print(load_info)
+   ```
+
+1. To load specific collections from the source incrementally:
+
+   ```python
+   load_data = mongodb(incremental=dlt.sources.incremental("date")).with_resources("collection_1")
+   load_info = pipeline.run(load_data, write_disposition = "merge")
+   print(load_info)
+   ```
+   > Data is loaded incrementally based on "date" field.
+
+1. To load data from a particular collection say "movies" incrementally:
+
+   ```python
+   load_data = mongodb_collection(
+     collection="movies",
+     incremental=dlt.sources.incremental(
+         "lastupdated", initial_value=pendulum.DateTime(2020, 9, 10, 0, 0, 0)
+     ))
+   
+   load_info = pipeline.run(load_data, write_disposition="merge")
+
+   ```
+
+   > The source function "mongodb_collection" loads data from a particular single 
+   > collection, where as source "mongodb" can load data from multiple collections. 
+   > This script configures incremental loading from the "movies" collection based on the
+   > "lastupdated" field, starting from midnight on September 10, 2020.
+
+1. To incrementally load a table with an append-only disposition using hints:
+
+   ```python
+   # Suitable for tables where new rows are added, but existing rows aren't updated.
+   # Load data from the 'listingsAndReviews' collection in MongoDB, using 'last_scraped' for incremental addition.
+   airbnb = mongodb().with_resources("listingsAndReviews")
+   
+   airbnb.listingsAndReviews.apply_hints(
+      incremental=dlt.sources.incremental("last_scraped")
+   )
+   info = pipeline.run(airbnb, write_disposition="append")
+
+   ```
+
+   > It applies hint for incremental loading based on the "last_scraped" field, ideal for tables
+   > with additions but no updates.
+
+1. To load a selected collection and rename it in the destination:
+
+   ```python
+    # Create the MongoDB source and select the "collection_1" collection
+    source = mongodb().with_resources("collection_1")
+
+    # Apply the hint to rename the table in the destination
+    source.resources["collection_1"].apply_hints(table_name="loaded_data_1")
+
+    # Run the pipeline
+    info = pipeline.run(source, write_disposition="replace")
+    print(info)
+   ```
diff --git a/docs/website/sidebars.js b/docs/website/sidebars.js
index 2551f5e6a4..9d17d6646b 100644
--- a/docs/website/sidebars.js
+++ b/docs/website/sidebars.js
@@ -45,6 +45,7 @@ const sidebars = {
             'dlt-ecosystem/verified-sources/hubspot',
             'dlt-ecosystem/verified-sources/jira',
             'dlt-ecosystem/verified-sources/matomo',
+            'dlt-ecosystem/verified-sources/mongodb',
             'dlt-ecosystem/verified-sources/mux',
             'dlt-ecosystem/verified-sources/notion',
             'dlt-ecosystem/verified-sources/pipedrive',