Faiss

Faiss

Meta
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About

Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research.

About

Open-source vector similarity search for Postgres. Supports exact and approximate nearest neighbor search for L2 distance, inner product, and cosine distance.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers interested in a similarity search library

Audience

Developers interested in an open source vector similarity search for Postgres

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Meta
Founded: 2004
United States
faiss.ai/

Company Information

pgvector
github.com/pgvector/pgvector

Alternatives

Alternatives

Embeddinghub

Embeddinghub

Featureform

Categories

Categories

Integrations

Cake AI
Haystack
LLMWare.ai
Langtrace
PostgreSQL
Supabase
Superexpert.AI

Integrations

Cake AI
Haystack
LLMWare.ai
Langtrace
PostgreSQL
Supabase
Superexpert.AI
Claim Faiss and update features and information
Claim Faiss and update features and information
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Claim pgvector and update features and information