Vector Database

A vector database stores high-dimensional embedding vectors alongside metadata and source references. At query time, it finds items whose vectors are close to the query vector, which often correspond to semantically similar text, images, or records.

Vector databases are commonly used in RAG, memory systems, semantic search, deduplication, and recommendation. Production designs still need permission filtering, freshness rules, metadata constraints, and evaluation of retrieval quality.