nmslib/hnswlib

Health v2 · maintenance only

Adoption not part of the score

5332 stars · 845 forks observed · 2026-09-23

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A header-only C++ library with Python bindings implementing the HNSW algorithm for fast approximate nearest neighbor search. It supports incremental index construction, updates, deletions, filtering, and custom distance functions with a small memory footprint.

Use cases

• find similar images by embedding vector
• build a vector index for semantic search
• fast k-nearest-neighbor search on millions of vectors
• deduplicate documents by embedding similarity
• recommendation engine candidate retrieval
• use as a lightweight local vector store for RAG

When to choose

• you need fast approximate nearest neighbor search in C++ or Python without heavy dependencies
• you need incremental insertions, updates, and deletions in a vector index
• memory footprint and build speed matter more than a full database with persistence and replication

When to avoid

• you need a distributed, persistent vector database with replication and filtering at scale
• you need exact (brute-force) nearest neighbor results
• you need a managed service or built-in REST API

Facets

library · maturity stable

search-engine machine-learning data-science machine-learning databases cpp python cross-platform approximate-nearest-neighbors ann hnsw vector-search header-only similarity-search embeddings search algorithms

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