Redis®*: Good to know

This documentation is part of the Vector search and RAG guide. You can view the complete guide here: Semantic search, recommendations, and retrieval-augmented generation with Redis.

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• Vector indexes only work on database 0, as with all search indexes in Redis.
• Vector sets offer a simpler alternative with no setup required. The VADD and VSIM commands are built into Redis, so you can use similarity search immediately, without enabling any modules. This is convenient for simple recommendation scenarios on a single set. The query engine remains preferable if you need filters, pagination, or multiple fields.
• Building an index over existing keys runs in the background. You can track progress with FT.INFO. Searches return partial results until indexing is complete.

To learn more about vector search in Redis, see the official Redis vector search documentation.