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pgvector

pgvector is a PostgreSQL extension that adds vector similarity search capabilities, enabling RAG systems and semantic search directly in your existing PostgreSQL database.

What Is pgvector?

pgvector turns PostgreSQL into a vector database — no additional infrastructure needed. Store embeddings alongside your regular data, run similarity searches with SQL, and benefit from PostgreSQL reliability, ACID compliance, and your existing backup/monitoring setup.

Key features: ivfflat and HNSW indexes for fast approximate nearest neighbor search, support for L2, inner product, and cosine distance, seamless integration with existing PostgreSQL queries, and the ability to filter results using standard SQL WHERE clauses.

pgvector vs Pinecone: pgvector is free, self-hosted, and integrates with your existing database. Pinecone is managed, scales automatically, but costs $70-700+/month. For most applications under 10 million vectors, pgvector is the better choice.

How Groovy Web Uses This

pgvector is our primary vector database for production RAG systems. We run it on our Supabase (PostgreSQL) infrastructure, processing millions of embeddings for enterprise clients.

Need Help with This?

Our AI-First engineers build production systems using pgvector technology. Talk to us.

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