What is vector database architecture in classification systems?

Vector database architecture stores and retrieves high-dimensional embeddings for similarity-based classification.

Vector databases like FAISS or Milvus enable fast nearest-neighbor search over embeddings. In classification systems, they are used for similarity-based labeling, retrieval-augmented classification, and zero-shot inference. They use approximate nearest neighbor (ANN) algorithms to scale to millions or billions of vectors efficiently.