Vector Databases
Some well-known vector databases are Pinecone, Milvus, Chroma, Weaviate, Qdrant, FAISS. General database systems like Elastic, Redis and Postgres (amongst others) also have some vector capabilities.
The main feature of a vector database is to be able to a vector-based query. Basically, you are looking for how close vectors are to each other in N-dimensional space. Cosine similarity is a common comparison, but other algorithms include nearest neighbors, least squares, and more.
Speed of the vector database lookup is obviously important for fast inference latency. Each vector also needs to be associated with the actual data or document in the database.