A vector database stores embeddings so a system can quickly find the records most similar in meaning to a new query.
Instead of searching for exact keyword matches, a vector database lets a system find the closest matching past quote, document, or record by meaning. A support system might use one to find similar past issues when a new customer complaint comes in.