Hybrid search combines full-text (BM25) and vector (KNN) search in a single query, covering the blind spots of each method. Manticore Search implements this using Reciprocal Rank Fusion (RRF), which merges ranked result lists without needing to normalize scores across different scales. The post explains when hybrid search is useful (RAG pipelines, mixed structured/unstructured data, unpredictable query patterns), walks through the RRF formula with concrete examples, and shows how to use Manticore's `hybrid_match()` shorthand or explicit MATCH+KNN syntax. Tuning options include rank_constant, fusion_weights, and window_size. Multi-vector fusion is also supported, enabling simultaneous search across text, title embeddings, and image embeddings with per-signal weighting.
Table of contents
What is hybrid search?How hybrid search fits into modern search pipelinesWhen should you use it?How it worksWhy not just use one or the other?Getting startedTuningMulti-vector fusionConclusionSort: