#55th of 8 in Vector databases
pgvector
PostgreSQL extension for vector similarity search with HNSW and IVFFlat
- Stars
- 23.3k
- License
- custom license
- Last commit
- Oct 2026
Overview
pgvector is a PostgreSQL extension (Postgres 13+) that adds vector, halfvec, bit and sparsevec column types with L2, inner product, cosine, L1, Hamming and Jaccard distance operators, exact search by default and HNSW or IVFFlat indexes for approximate search. Vectors sit beside ordinary rows with ACID, joins and backups, and Postgres full-text search can be combined for hybrid retrieval. It installs via make, Docker or OS packages.
Who it is for: teams already on Postgres who want vectors without a new database
Strengths
- Vectors live next to relational data with ACID, joins and point-in-time recovery
- HNSW and IVFFlat indexes with six distance operators
- Half-precision, binary and sparse vector types plus binary quantization
- Installs via make, Docker, Homebrew, APT, Yum; preinstalled on many hosted Postgres
Weaknesses
- vector type capped at 2,000 dimensions (halfvec 4,000)
- Approximate indexes filter after scanning; filtered recall needs iterative scan tuning
- HNSW builds slow down sharply once the graph exceeds maintenance_work_mem
- No server of its own; capacity depends on your Postgres tuning
What it needs
- no GPU
- Docker
- Needs PostgreSQL 13+
- Models: any embedding model; stores precomputed vectors
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