[{"data":1,"prerenderedAt":12},["ShallowReactive",2],{"stack-tr-en-qdrant":3},{"tagline":4,"description":5,"strengths":6,"useCase":11},"The open source vector database in Rust for semantic search at scale.","Qdrant is an open source vector database written in Rust: it indexes embeddings and serves low-latency similarity search, even across millions of vectors. Payload filtering combines semantics and business criteria in one query, and hybrid search (dense + sparse) sharpens relevance. Managed cloud or self-hosted, it's our choice when a RAG pipeline has to handle real load or stay on your own infrastructure.",[7,8,9,10],"Written in Rust: performance and low memory footprint at scale.","Payload filtering: semantics + business criteria in one query.","Hybrid dense + sparse search, quantization and multi-tenancy.","Managed cloud or self-hosted (Docker, Kubernetes): sovereignty possible.","Production RAG, semantic search, recommendation, deduplication.",1792592358445]