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feat: support pgvector extension #445
feat: support pgvector extension #445
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Hi @mrdrivingduck ~ Thanks for your contribution in this PR. ❤️ Please make sure that your PR conforms the standard, and has passed all the checks. We will review your PR as soon as possible. |
Hey @mrdrivingduck : Something wrong occuried during the checks of your commit 😟, please check the detail:
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Hey @mrdrivingduck : Something wrong occuried during the checks of your commit 😟, please check the detail:
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Hey @mrdrivingduck : Congratulations~ 🎉 Your commit has passed all the checks. Please wait for further manual review. |
The pgvector plugin is a plugin for PostgreSQL that provides high-performance vector data types and related query capabilities. This plugin makes it more efficient and convenient to store and process vector data in PostgreSQL. Here are some features and functionalities of the pgvector plugin: 1. Vector data type: The pgvector plugin introduces a new data type called "vector" that can be used to store and manipulate The pgvector plugin is a plugin for PostgreSQL that provides high-performance vector data types and related query capabilities. This plugin makes it more efficient and convenient to store and process vector data in PostgreSQL. Here are some features and functionalities of the pgvector plugin: 1. Vector data type: The pgvector plugin introduces a new data type called "vector" that can be used to store and manipulate high-dimensional vector data. 2. Vector indexing: pgvector provides support for indexing and querying vector data, making it easier to perform similarity searches, clustering, and classification operations on vector data. The plugin supports GIN and GiST index types. 3. Vector operations: pgvector provides a range of vector operation functions, allowing for addition, subtraction, dot product calculation, and length calculation between vectors. 4. Similarity search: The pgvector plugin supports similarity searches based on vector similarity metrics. It enables similarity calculation and search using cosine similarity and other measurement methods. 5. High performance: pgvector is optimized for vector data by utilizing SIMD instructions and efficient data structures, ensuring high-performance vector operations and queries. 6. Extensibility: As an open-source project, the pgvector plugin offers flexible custom extension interfaces, allowing users to customize and extend its functionality based on their specific needs.
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Hey @mrdrivingduck : Congratulations~ 🎉 Your commit has passed all the checks. Please wait for further manual review. |
/rebase-and-merge |
@mrdrivingduck PR has been merged. 🍗 Thanks again for the contributors involved in this thread: ❤️ |
The pgvector plugin is a plugin for PostgreSQL that provides high-performance vector data types and related query capabilities. This plugin makes it more efficient and convenient to store and process vector data in PostgreSQL.
Here are some features and functionalities of the pgvector plugin:
The pgvector plugin is a plugin for PostgreSQL that provides high-performance vector data types and related query capabilities. This plugin makes it more efficient and convenient to store and process vector data in PostgreSQL.
Here are some features and functionalities of the pgvector plugin:
Vector data type: The pgvector plugin introduces a new data type called "vector" that can be used to store and manipulate high-dimensional vector data.
Vector indexing: pgvector provides support for indexing and querying vector data, making it easier to perform similarity searches, clustering, and classification operations on vector data. The plugin supports GIN and GiST index types.
Vector operations: pgvector provides a range of vector operation functions, allowing for addition, subtraction, dot product calculation, and length calculation between vectors.
Similarity search: The pgvector plugin supports similarity searches based on vector similarity metrics. It enables similarity calculation and search using cosine similarity and other measurement methods.
High performance: pgvector is optimized for vector data by utilizing SIMD instructions and efficient data structures, ensuring high-performance vector operations and queries.
Extensibility: As an open-source project, the pgvector plugin offers flexible custom extension interfaces, allowing users to customize and extend its functionality based on their specific needs.