FAISS
Meta's open-source library for efficient similarity search and dense vector clustering
FAISS (Facebook AI Similarity Search) is the most widely-used open-source library for efficient similarity search over dense vectors. It supports billion-scale datasets with GPU acceleration, multiple index types (IVF, HNSW, PQ), and both exact and approximate nearest neighbor search. Used as the core search engine in many vector database and RAG implementations.
Pricing: Free
FAISS Alternatives
Explore 25 products in the Vector databases category. View all FAISS alternatives.
Supabase Vector
Open-source Postgres vector database and AI toolkit built on pgvector
Milvus
Vector database built for scalable similarity search.
TopK
AI-native search engine combining vector, keyword, and faceted search
Elasticsearch
Distributed full-text search and analytics engine with built-in vector and hybrid search
Redis
In-memory vector database for low-latency similarity search across AI applications
Cloudflare Vectorize
Serverless vector database on Cloudflare's global network
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