pgvector

pgvector is a local-AI tool - Open-source vector similarity search for Postgres.

Overview

You can also install it with Docker, Homebrew, PGXN, APT, Yum, pkg, APK, or conda-forge, and it comes preinstalled with Postgres.app and many hosted providers. There are also instructions for GitHub Actions.

Ensure C++ support in Visual Studio is installed and run 'x64 Native Tools Command Prompt for VS [version]' as administrator. Then use 'nmake' to build:

By default, pgvector performs exact nearest neighbor search, which provides perfect recall.

You can add an index to use approximate nearest neighbor search, which trades some recall for speed. Unlike typical indexes, you will see different results for queries after adding an approximate index.

An HNSW index creates a multilayer graph. It has better query performance than IVFFlat (in terms of speed-recall tradeoff), but has slower build times and uses more memory. Also, an index can be created without any data in the table since there isn’t a training step like IVFFlat.

A higher value of 'ef_construction' provides better recall at the cost of index build time / insert speed.

An IVFFlat index divides vectors into lists, and then searches a subset of those lists that are closest to the query vector. It has faster build times and uses less memory than HNSW, but has lower query performance (in terms of speed-recall tradeoff).

pgvector is open-source, written primarily in C, with 23,307 GitHub stars under the Other license. It was last updated on 2026-10-08.

Key capabilities

From the project's documentation:

• exact and approximate nearest neighbor search
• single-precision, half-precision, binary, and sparse vectors
• L2 distance, inner product, cosine distance, L1 distance, Hamming distance, and Jaccard distance
• any language with a Postgres client
• • (negative) inner product
• • Hamming distance (binary vectors)

How it fits a local-AI stack

pgvector runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related local-AI tools in the directory:

• "algernon"
• "blinko"
• Continue
• "exo"

Sources

• Source code & docs: pgvector/pgvector

Stats from GitHub, 2026-10-12.