Quick answer: OSS vector DB written in Rust — fast filtering + payload.
Qdrant is an open-source vector database written in Rust, designed for fast similarity search and vector storage at scale. Built by Qdrant, the tool specializes in indexing and querying high-dimensional vectors with advanced filtering capabilities—a critical component in modern AI and machine learning applications. Unlike traditional databases optimized for structured data, Qdrant handles vector embeddings efficiently, supporting semantic search, recommendation systems, and retrieval-augmented generation (RAG) pipelines. The database emphasizes performance, scalability, and payload filtering, allowing you to attach and filter on metadata alongside vector similarity. Qdrant offers both open-source self-hosted deployment and a managed cloud service, making it accessible for projects ranging from prototypes to production systems handling millions of vectors.