FAISS
Meta's library for efficient similarity search and clustering of dense vectors — the indexing primitive behind many vector DBs.
vector-database-frameworksRecently released
63
Hero Score
Popularity
80
Performance
60
Ecosystem
50
Maturity
77
Dev Experience
50
⭐ 40,176 stars⬇ 3.8M downloads/wkFirst release: Jul 2019Last release: May 2026
Async Support: NoPlugin Extensions: MediumSpeed: Very fastDoc Quality: HighLearning Curve: Hard
Pros
- • Battle-tested raw-speed champion — powers indexing inside many higher-level vector DBs
- • Wide range of index types (Flat, IVF, HNSW, PQ, OPQ) for tuning recall vs speed
- • GPU acceleration available via `faiss-gpu` for very large in-memory workloads
Cons
- • Library, not a database — no server, persistence layer, filtering, or metadata out of the box
- • Steeper learning curve to choose and tune the right index type for your data
- • GPU variant (`faiss-gpu`) requires a separate package and CUDA setup