Faiss vs hnswlib
Faiss: Meta's C++/Python library for fast dense-vector similarity search and clustering, CPU and GPU. hnswlib: Header-only C++ HNSW library with Python bindings, from the authors of the HNSW algorithm.
key differences
- Faiss is built for larger datasets (≤ 1 PB) than hnswlib (≤ 10 TB).
- Only Faiss has compression.
choose faiss for
- +Embedding similarity search inside ML pipelines
- +Offline deduplication and clustering
- +Building custom vector search services
- +ANN research and benchmarking
best at · Vector search, Embedded, Scientific
choose hnswlib for
- +Embedding HNSW in applications
- +Baseline for ANN benchmarks
- +Small in-process semantic search
best at · Vector search, Embedded
Faiss vs hnswlib: FAQ
What is the difference between Faiss and hnswlib?
Faiss: Meta's C++/Python library for fast dense-vector similarity search and clustering, CPU and GPU. hnswlib: Header-only C++ HNSW library with Python bindings, from the authors of the HNSW algorithm. Faiss is built for larger datasets (≤ 1 PB) than hnswlib (≤ 10 TB). Only Faiss has compression.
When should I choose Faiss over hnswlib?
Choose Faiss for embedding similarity search inside ML pipelines; offline deduplication and clustering; and building custom vector search services. Choose hnswlib for embedding HNSW in applications, baseline for ANN benchmarks and small in-process semantic search.
Is Faiss or hnswlib more popular?
Faiss ranks #40 on the WhichDB Score (44.7/100) and hnswlib ranks #211 (15.5/100). Popularity is not fit: check the requirements that matter for your project.
Are Faiss and hnswlib open source?
Yes. Faiss is open source. License: MIT License. Yes. hnswlib is open source. License: Apache License 2.0.