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.
Azure AI Search
Microsoft managed search service with vector, hybrid, and agentic retrieval for RAG
Elasticsearch
Distributed full-text search and analytics engine with built-in vector and hybrid search
Cloudflare Vectorize
Serverless vector database on Cloudflare's global network
Typesense
Open-source typo-tolerant search engine with built-in vector and hybrid search
Vespa
Open-source search and serving engine combining vector search, keyword search, and ML ranking at scale
OpenSearch
Open-source search and analytics suite with full-text, vector, and hybrid search
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