# currentslab/awesome-vector-search

Collections of vector search related libraries, service and research papers

Repository: https://github.com/currentslab/awesome-vector-search
Canonical: https://ross.abutalabs.com/products/awesome-vector-search
License: MIT
License Family: permissive
Topics: awesome-list, awesome, vector, similarity-search, vector-search-engine, nearest-neighbor-search, vector-search, knn-search, machine-learning, search-engine
Last push: 2026-07-06T04:12:57+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 91, release rhythm 35, longevity 100
- inputs: {"age_days": 1972, "days_push": 58, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1581, forks 128 (observed 2026-08-28T04:05:07.050999+00:00)

## What it is
A curated awesome list of vector search engines, libraries, cloud services, and research papers. It catalogs resources for vector similarity and nearest-neighbor search rather than being software itself.

## Use cases
- find a vector database for my project
- compare vector search engines and libraries
- learn about approximate nearest neighbor search
- find research papers on similarity search
- discover vector search cloud services
- choose an ANN library for embeddings

## When to choose
- you are researching options for vector similarity search
- you want a broad overview of the vector search ecosystem
- you need references to papers and tools in one place

## When to avoid
- you need runnable software rather than a link collection
- you need guaranteed up-to-date or benchmarked comparisons

## Facets
- artifact type: learning-resource
- maturity: active
- function: vector-database, search-engine
- domain: databases, machine-learning, awesome-lists
- platform: cross-platform
- tags: awesome-list, vector-search, similarity-search, nearest-neighbor, curated-resources, research-papers, search

## Member repositories
- currentslab/awesome-vector-search (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:07.050999+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 2026-08-30T03:56:33.015040+00:00, confidence not recorded.
  - readme: https://github.com/currentslab/awesome-vector-search (fetched 2026-08-28T04:05:07.050999+00:00, sha b459fb5ef096)
- Data as of 2026-08-30T08:39:29.467469+00:00.