# VexDB-THU/VexDB-Lite

A cross-platform vector database, which can be integrated into existing databases as a plugin.

Repository: https://github.com/VexDB-THU/VexDB-Lite
Canonical: https://ross.abutalabs.com/products/vexdb-lite
Homepage: https://vexdb.com
Language: C++
License: MIT
License Family: permissive
Last push: 2026-08-25T10:16:21+00:00

## Health v2 (maintenance only)
Score: 80/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 95, longevity 12
- inputs: {"age_days": 170, "days_push": 8, "days_rel": 35, "gap_med": 1.5, "n_releases_24m": 5}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2275, forks 353 (observed 2026-08-28T04:06:33.303348+00:00)

## What it is
VexDB-Lite is a cross-platform vector similarity search engine implemented as plugins for PostgreSQL, DuckDB, and SQLite, sharing a graph index algorithm, SIMD distance dispatch, and PQ/RaBitQ quantization kernels. It provides vector types, distance operators, graph indexes with metadata filtering, and optimizer-integrated ANN index scans.

## Use cases
- add vector similarity search to postgres
- semantic search over embeddings in sqlite
- nearest neighbor search in duckdb
- store and query embeddings alongside relational data
- run vector search on mobile or in the browser with sqlite/wasm
- compress vector indexes with pq or rabitq quantization

## When to choose
- you want ANN search inside an existing PostgreSQL, DuckDB, or SQLite database rather than a separate vector database
- you need cross-platform support including mobile and WASM via SQLite
- you need quantized (PQ/RaBitQ) compact index storage to reduce memory

## When to avoid
- you need a standalone distributed vector database with sharding and high availability - use the commercial VexDB or alternatives like Milvus
- you need BM25 hybrid full-text plus vector retrieval out of the box - the Lite plugins focus on vector search
- you require non-SQL databases such as MongoDB or Redis

## Facets
- artifact type: library
- maturity: active
- function: vector-database, database, search-engine, database-driver
- domain: databases, machine-learning, developer-tools
- platform: windows, wasm, cpp, cross-platform
- tags: ann-search, hnsw, postgresql-extension, duckdb-extension, sqlite-extension, quantization, embeddings, similarity-search, search, linux, macos, android, ios

## Member repositories
- VexDB-THU/VexDB-Lite (main) score 80

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:33.303348+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:41:28.596706+00:00, confidence not recorded.
  - readme: https://github.com/VexDB-THU/VexDB-Lite (fetched 2026-08-28T04:06:33.303348+00:00, sha b6e7e7e16555)
  - homepage: https://vexdb.com (fetched 2026-08-29T10:22:00.377484+00:00, sha 93a92c94c805)
  - site_page: https://vexdb.com/docs/about/introduction (fetched 2026-08-29T10:22:00.386664+00:00, sha 709509d4cfaa)
- Data as of 2026-08-30T08:39:29.467469+00:00.