Vector Database

Vector databases form the infrastructure layer for embedding-based retrieval in modern AI applications. Once documents, images, products, or user behaviors are converted into numerical vector representations, they must be searched quickly and meaningfully. Traditional relational databases typically do not perform well for this use case. Vector databases play a central role in nearest-neighbor search, metadata-aware filtering, and retrieval-driven AI architectures.