Qdrant

High-performance vector search at scale

Qdrant is a vector similarity search engine and database designed for AI applications. Built in Rust for performance and reliability, it offers native hybrid search combining dense and sparse vectors, advanced metadata filtering, and multivector support for complex similarity queries. The company serves production AI workloads for enterprises including Canva, HubSpot, OpenTable, and Deutsche Telekom. With over 250 million downloads and 29K+ GitHub stars, Qdrant has become a core infrastructure component for RAG pipelines, AI agents, and multimodal retrieval systems. Beyond the core vector database, Qdrant offers FastEmbed for lightweight embedding generation, Qdrant Cloud for fully managed deployments, and Qdrant Edge for low-latency vector search at the edge. The company raised a $50M Series B in March 2026 led by AVP with participation from Bosch Ventures, Spark Capital, and others.