Vector database
A vector database stores embedding vectors and retrieves nearest neighbours for semantic search and RAG pipelines.
How it works
You upsert vectors with metadata, query by similarity, and filter by tenant or tag. Operational concerns include re-indexing, deletion and tenancy isolation.
Example
A multi-tenant help center keeps each customer's vectors isolated with metadata filters on every query.