9.3 Redis as a Vector Store

An embedding model converts text, images, or other data into a vector of hundreds or thousands of numbers, and it places the vectors so that similar items are close together. Search then becomes a geometric question: which stored vectors are nearest to the query vector? Exact nearest-neighbor search compares the query with every stored vector, which is too slow for large collections, so vector stores build approximate nearest neighbor (ANN) indexes instead