Do you know about vector databases?

A vector database is a specialized database that stores high-dimensional vectors and supports efficient similarity search operations such as nearest neighbor queries. Unlike traditional relational databases that index scalar values, vector databases use approximate nearest neighbor (ANN) algorithms like HNSW, IVF, or PQ to quickly retrieve vectors that are close in Euclidean or cosine distance. They are commonly used in recommendation engines, image and text embeddings, and AI applications where you need to find similar items in large embedding spaces. Popular open-source vector stores include Milvus, Faiss, and Annoy, while cloud offerings include Pinecone and AWS Bedrock. The key benefits are low latency, high scalability, and the ability to handle millions of vectors with sub‑millisecond query times.