Best Vector Databases for PostgreSQL
PostgreSQL is the world's most advanced open-source relational database, and its ecosystem now includes powerful vector search capabilities. If your application already runs on Postgres, you can add vector search without introducing a new database. pgvector, Supabase Vector, and other PostgreSQL-based solutions let you store embeddings alongside your relational data, query with familiar SQL, and maintain ACID transactions across your entire dataset.
5 databases compatible with PostgreSQL
Why use PostgreSQL with a vector database?
PostgreSQL is the world's most advanced open-source relational database, and its ecosystem now includes powerful vector search capabilities. If your application already runs on Postgres, you can add vector search without introducing a new database. pgvector, Supabase Vector, and other PostgreSQL-based solutions let you store embeddings alongside your relational data, query with familiar SQL, and maintain ACID transactions across your entire dataset.
How to get started with PostgreSQL
- 1Enable pgvector in your PostgreSQL instance: CREATE EXTENSION vector;
- 2Create a table with a vector column: embedding vector(1536)
- 3Insert embeddings alongside your relational data using standard SQL INSERT
- 4Query with similarity search: SELECT * FROM items ORDER BY embedding <=> query_vector LIMIT 10;
FAQ — PostgreSQL & Vector Databases
Should I use pgvector or a dedicated vector database?
Use pgvector if you already run PostgreSQL and have under ~10M vectors. For larger scale, higher QPS, or advanced vector features, consider a dedicated database like Qdrant, Pinecone, or Milvus.
What is the difference between pgvector and Supabase Vector?
Supabase Vector uses pgvector under the hood but adds a managed platform with authentication, APIs, and a dashboard. pgvector is the raw PostgreSQL extension you install on any Postgres instance.
Can pgvector handle production workloads?
Yes. pgvector with HNSW indexes handles millions of vectors efficiently. Companies like Supabase and Neon run pgvector at scale. For billions of vectors or very high QPS, consider a purpose-built vector database.
Does pgvector support filtering with vector search?
Yes. Since pgvector runs inside PostgreSQL, you can combine vector similarity search with standard SQL WHERE clauses, JOINs, and aggregations in a single query.