Qdrant is an open-source vector similarity search engine and database written in Rust. It supports a wide range of text and multimodal dense vector embedding models. Our teams have used open-source embeddings like MiniLM-v6 and BGE for multiple product knowledge bases. We use Qdrant as an enterprise vector store with multi-tenancy to store vector embeddings as separate collections, isolating each product's knowledge base in storage. User access policies are managed in the application layer.
Qdrant is an open-source vector database written in Rust. In the September 2023 edition of the Radar, we talked about pgvector, a PostgreSQL extension for vector search. However, if you have to scale the vector database horizontally across nodes, we encourage you to assess Qdrant. It has built-in single instruction, multiple data (SIMD) acceleration support for improved search performance, and it helps you associate JSON payloads with vectors.
