Numeric Range Queries And Aggregations

via “numeric range indexing and range query filtering”

Instant search engine with vector support.

Unique: Uses NumericTrie data structure specifically optimized for range queries, providing O(log n) range query performance. Integrates range filtering directly into the search pipeline alongside text search and faceting.

vs others: More efficient range queries than Elasticsearch's range filters (which use inverted index scans); simpler API than Solr's numeric range queries; native support for both integer and floating-point ranges.

A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.

Unique: Uses a specialized numeric range tree (not a B-tree or skip list) optimized for Redis' in-memory model, combined with aggregation pipeline that supports expression evaluation (src/result_processor.h) for computed fields during aggregation, enabling complex numeric transformations without post-processing

vs others: Faster than SQL databases for numeric range queries on indexed fields because the range tree is optimized for in-memory traversal; more flexible than simple hash-based filtering because it supports arbitrary range bounds without pre-computed buckets