Qdrant
qdrant.techHigh-Performance Vector Search Engine for Production-Grade AI Search
Dev Toolsvector-searchopen-sourcerustai-infrastructureembeddingssimilarity-searchrag
About
Qdrant is an open-source vector search engine written in Rust, designed for fast and scalable similarity search at any scale. It supports hybrid search (dense + sparse vectors), metadata filtering, multitenancy, quantization, and real-time indexing. It can be self-hosted or deployed via Qdrant Cloud, integrating with popular AI frameworks for use cases like RAG, semantic search, and recommendation systems.
Problem
Building fast, scalable vector similarity search for AI applications requires specialized infrastructure that general-purpose databases cannot efficiently provide.
For
AI engineers and developers building production-grade search and retrieval systems
How it works
Qdrant stores vectors alongside metadata in a custom Rust-based storage engine with HNSW indexing, enabling sub-millisecond similarity search with advanced filtering, hybrid search, and quantization via REST or gRPC APIs.
Business model
freemium
Status
launched