pgvector

Open-source vector similarity search for Postgres.

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Overview

pgvector is an open-source extension for PostgreSQL that adds the ability to store and query vector embeddings. It allows you to perform nearest neighbor search in your existing PostgreSQL database, making it easy to add vector search capabilities to applications built on Postgres.

✨ Key Features

  • Open-source PostgreSQL extension
  • Exact and approximate nearest neighbor search
  • Supports L2 distance, inner product, and cosine distance
  • Indexing for performance
  • Works with existing PostgreSQL features

🎯 Key Differentiators

  • Seamless integration with PostgreSQL
  • Leverages the robustness and maturity of the PostgreSQL ecosystem
  • No need for a separate database for vector search

Unique Value: pgvector allows you to leverage your existing PostgreSQL database for vector similarity search, simplifying your architecture and reducing operational overhead.

🎯 Use Cases (3)

Adding vector search to existing PostgreSQL applications Semantic search Recommendation systems

✅ Best For

  • Implementing semantic search in a web application with a PostgreSQL backend
  • Building a simple recommendation engine within an existing database

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Large-scale, high-throughput vector search applications that may be better served by a specialized vector database.

🏆 Alternatives

Specialized vector databases (Pinecone, Milvus, etc.)

For teams already using PostgreSQL, pgvector is a much simpler and more integrated solution than setting up and maintaining a separate, specialized vector database.

💻 Platforms

API

✅ Offline Mode Available

🔌 Integrations

PostgreSQL LangChain LlamaIndex Any application that uses PostgreSQL

💰 Pricing

Contact for pricing
Free Tier Available

Free tier: Open-source and free to use.

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