TL;DR — pgvector adds vector similarity search to PostgreSQL so you can keep metadata and vectors in one system.
What it is
It is a Postgres extension with operators for cosine, L2, and inner product search.
Why it exists
Use pgvector when your team already runs Postgres and wants fewer moving pieces.
Install
CREATE EXTENSION IF NOT EXISTS vector;Basic usage
-- store embedding in vector column
-- query with ORDER BY embedding <-> query_embedding LIMIT kWhen to use, when to skip
Use it when this category is a bottleneck in your agent stack and you want faster delivery with fewer custom components.
Skip it when your workload is tiny, requirements are fixed, or a plain provider SDK plus a few local functions is enough.
Alternatives
Compare with adjacent tools in the same AI Native category and choose based on interface style, deployment model (hosted vs self-hosted), and team familiarity.
Verified against project documentation, June 2026.