What is a prefetch stage in Qdrant's Universal Query API, and why would you use multiple prefetches?

A prefetch is an earlier retrieval stage that generates candidate points for a later query stage. Instead of immediately returning the first search result, Qdrant can retrieve a larger candidate set and then use those points as the input to fusion or reranking.

Multiple prefetches are useful when candidate generation comes from different retrieval signals. A common example is dense semantic retrieval plus sparse lexical retrieval. Each prefetch can retrieve its own candidates, after which Qdrant can fuse or rerank the combined candidate set.

The key engineering reason is recall first, precision second. Cheap retrieval stages can cast a wide net, while a more expensive reranker operates on a smaller candidate set. The trade-off is additional computation and latency, so candidate limits should be tuned against end-to-end quality.

A common mistake is assuming prefetch means fetching data from another database. It is a retrieval stage within the Qdrant query execution plan. The exact nesting and supported combinations depend on the Qdrant version.