RediSearch is a Redis module that provides query ability, secondary indexing, and full-text search for Redis data stored as Redis hashes or JSON format. With Redis 2.4, Redis introduced support for vector similarity search. With RediSearch 2.4, Redis developers can: - Index and query vector data stored as BLOBs in Redis hashes - Use two popular indexing methods: FLAT and HNSW - Use three common vector distance metrics: cosine, internal product, and euclidean distance - Perform hybrid queries which combine vector similarity with traditional RediSearch filtering capabilities on GEO, NUMERIC, TAG, or TEXT data. A common example of a hybrid query in an e-commerce setting is "find items visually similar to a given query image limited to items available in a GEO location and within a price range".