Qdrant Vector Search

A production-grade vector database that actually scales, built in Rust for speed. You get hybrid search with dense, sparse, and multi-vector storage, plus real filtering during queries instead of just post-processing. The HNSW indexing keeps nearest-neighbor search fast even at scale, and quantization options help you manage memory when datasets balloon. Works with the usual suspects like LangChain and LlamaIndex, exposes both REST and gRPC APIs, and supports distributed deployment with sharding when a single box won't cut it. If you're moving a RAG system to production or need semantic search that won't fall over under load, this is the right foundation.