In plain English
Instead of looking up records only by exact values or keywords, a vector database can search by mathematical similarity. That makes it useful when an application needs to find text, images, or other data that are conceptually similar to a query.
Example
A RAG assistant could store embeddings for thousands of internal documents in a vector database and retrieve the most relevant passages before generating an answer.