So Sánh Vector Database Cho RAG: Qdrant vs Milvus vs pgvector trong Production
← Chương trước: Kiến Trúc Bảo Mật Zero-Trust Cho Microservices | Mục lục Series | Chương tiếp theo: Cloudflare Workers & Edge Computing → Answer-first: A Vector Database indexes high-dimensional embeddings using algorithms like Hierarchical Navigable Small World (HNSW) for ultra-fast semantic retrieval. In modern RAG architectures, combining dense semantic vectors with sparse BM25 keyword vectors via Reciprocal Rank Fusion (RRF) delivers optimal retrieval accuracy while Scalar and Binary Quantization reduce memory footprints up to 32x without degrading latency. ...