🦀 Qdrant - Vector Database

Qdrant is a high-performance vector similarity search engine and vector database written in Rust. It is designed to handle high-dimensional vector embeddings with millisecond-level latency, making it the perfect memory layer for RAG (Retrieval-Augmented Generation) and semantic search applications in 2026. Qdrant provides a robust API for storing, searching, and managing vectors with additional payload filtering. Its architecture allows for vertical and horizontal scaling, supporting billion-scale datasets. By self-hosting Qdrant, developers can ensure that their sensitive vector data—representing the collective knowledge of their organization—remains private and secure, avoiding the high costs and privacy risks of managed cloud vector stores.