pgvector
pgvector projectpgvector is a Postgres extension that adds vector types and similarity search to the database, supporting exact and approximate nearest neighbour queries over single-precision, half-precision, binary and sparse vectors with L2, inner-product, cosine, L1, Hamming and Jaccard distances. Vectors live in ordinary tables, so joins, transactions and point-in-time recovery apply to them.
Verified 2026-08-18 via the GitHub API and the LICENSE body.
Openness
5 high confidence- license
- PostgreSQL(OSI)
- source
- public
- core-gated
- ungated
The LICENSE body is the PostgreSQL License - the Postgres project's own permissive terms, carrying the University of California and PostgreSQL Global Development Group notices, and OSI-approved. The repository is public and unarchived and builds the whole extension, and the README describes no paid tier or license-gated build beside it, so source is public and the core ungated. The shared software ladder's OSI tier lists license names literally, so this license mapped to no tier and the formula abstained until the tier was extended to name it on the owner's ruling. pgvector was the first product on the map to record it, so the ruling moved no existing score, and the ladder now reproduces this one rather than deferring it.
- https://github.com/pgvector/pgvector/blob/master/LICENSE recorded 2026-08-18
LICENSE body is the PostgreSQL License - the Postgres project's own permissive terms, carrying the PostgreSQL Global Development Group and University of California notices - which is why the API reports NOASSERTION.
- https://api.github.com/repos/pgvector/pgvector recorded 2026-08-18
Repo metadata - license spdx_id NOASSERTION, private false, archived false, default branch master - for pgvector/pgvector.
- https://github.com/pgvector/pgvector/blob/master/README.md recorded 2026-08-18
README describes vector similarity search for Postgres with exact and approximate nearest neighbour search over single-precision, half-precision, binary and sparse vectors, six distance metrics, quantization for scale, and ACID compliance and point-in-time recovery inherited from Postgres, with no paid tier, enterprise edition or license-key-gated build beside it.
Adoption
3 low confidence22,664 GitHub stars, which lands in the >10K stars band of the stars scale, level 3. The `pgvector` package on PyPI is pgvector-python, a client helper for talking to the extension from Python, and its 36.6M monthly downloads belong to that library rather than to this one. The extension itself is distributed through distribution packages, PGXN and managed-Postgres vendors, none of which publishes a comparable count, so the stars scale applies with its cap of 3.
- https://api.github.com/repos/pgvector/pgvector recorded 2026-08-18
Repo metadata - stargazers_count = 22,664 - for pgvector/pgvector.
Capability
3 medium confidenceBanded on the category feature matrix as single-purpose store or index. Placed two bands below the vespa anchor, on a matrix that bands on how much of the persist-index-retrieve path a product provides itself, at what scale and over how many retrieval modes.
- https://github.com/pgvector/pgvector/blob/master/README.md recorded 2026-08-18
README still documents vector similarity search for Postgres with exact and approximate nearest neighbour search over single-precision, half-precision, binary and sparse vectors, six distance metrics, quantization for scale, and ACID compliance and point-in-time recovery inherited from Postgres.
Verified 2026-08-18