Update 07/2026 (trial → adopt): Qdrant has proven itself in production and remains one of our first choices when a dedicated, self-hostable vector database is needed - especially for data-sovereign setups.
Qdrant continued strong development: v1.17 added agent-oriented primitives, v1.18 (May 2026) brought TurboQuant quantization and dynamic named vectors (Releases).
Qdrant is a powerful open-source vector database designed for semantic search, similarity queries, and Retrieval-Augmented Generation (RAG).
Written in rust, it has a focus on performance, scalability, and API accessibility, making it a good choice for teams building high-performance vector storage in production environments.
It offers flexible deployment options, customizability, and advanced search features, making it ideal for building data sovereign AI applications.