Related projects

This page references other projects and repositories that use Faiss or that are related to it. They are unaffiliated the main Faiss, so any issue with those should be redirected to the respective packages. If you did something interesting with Faiss and you want to add a link to your project, just ask us (via an issue).

Bindings to other languages

There are projects to interface Faiss with other languages, see

• the Rust bindings at https://github.com/Enet4/faiss-rs

• the .NET Core 3.0 bindings at https://gitlab.com/josetruyol/faisssharp

Faiss is reported to work on Raspberry Pi (see https://github.com/facebookresearch/faiss/issues/1071)

Packages that use or extend Faiss

• QuickerADC, an implementation of IVFPQ variants using SIMD with better precision/speed operating points: https://github.com/technicolor-research/faiss-quickeradc See also the paper Quicker ADC : Unlocking the hidden potential of Product Quantization with SIMD, André et al.

• pgANN: Approximate Nearest Neighbor (ANN) searches with a PostgreSQL database. https://github.com/netrasys/pgANN

• milvus offers a uniform interface to Faiss + other packages and manages it like a database engine (client/server and the like): https://github.com/milvus-io/milvus

• vearch: a search engine based on Faiss with good scalability and real-time updates: https://github.com/vearch/vearch

• port of (an old version of) Faiss to Windows: https://github.com/bitsun/faiss-windows

Alternative packages

There are many approximate nearest neighbor search libraries. You may be interested in:

• NMSLib (An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces): https://github.com/nmslib/nmslib

• an implementation of IVF-HNSW https://github.com/dbaranchuk/ivf-hnsw

• Annoy (Approximate Nearest Neighbors in C++/Python): https://github.com/spotify/annoy

• Approximate nearest neighbor benchmark page: https://github.com/erikbern/ann-benchmarks

• A promising GPU index here (vaporware as of 2020-01-20): https://github.com/cgtuebingen/ggnn