RediSearch
RediSearch/RediSearch
A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.
Overview
RediSearch is a powerful Redis module offering advanced querying capabilities including full-text search and vector similarity searches. It enhances Redis by adding functionalities such as exact-phrase matching, fuzzy search, numeric filtering, aggregations, and more.
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Install
git clone https://github.com/RediSearch/RediSearchREADME
RediSearch
| Total Coverage | Unit Tests | Flow Tests |
|---|---|---|
[!NOTE] Starting with Redis 8, Redis Query Engine (RediSearch) is integral to Redis. You don't need to install this module separately.
We no longer release standalone versions of RediSearch.
See https://github.com/redis/redis for more information.
[!NOTE] 32 bit systems are not supported.
Overview
RediSearch is a Redis module that provides querying, secondary indexing, and full-text search for Redis. To use RediSearch, you first declare indexes on your Redis data. You can then use the RediSearch query language to query that data.
RediSearch uses compressed, inverted indexes for fast indexing with a low memory footprint.
RediSearch indexes enhance Redis by providing exact-phrase matching, fuzzy search, and numeric filtering, among many other features.
Getting started
If you're just getting started with RediSearch, check out the official RediSearch tutorial. Also, consider viewing our RediSearch video explainer.
Documentation
The RediSearch documentation provides a complete overview of RediSearch. Helpful sections include:
- The RediSearch quick start
- The RediSearch command reference
- References on features such as aggregations, highlights, stemming, and spelling correction.
- [Vector search] (https://redis.io/docs/latest/develop/interact/search-and-query/query/vector-search/)
Questions?
Got questions? Join us in #redisearch on the Redis Discord server.
RediSearch features
- Full-Text indexing of multiple fields in Redis hashes
- Incremental indexing without performance loss
- Document ranking (using BM25 as default, with optional user-provided weights). All available scoring methods described here
- Field weighting
- Complex boolean queries with AND, OR, and NOT operators
- Prefix matching, fuzzy matching, and exact-phrase queries
- Support for double-metaphone phonetic matching
- Auto-complete suggestions (with fuzzy prefix suggestions)
- Stemming-based query expansion in many languages (using Snowball)
- Support for Chinese-language tokenization and querying (using Friso)
- Numeric filters and ranges
- Geospatial searches using Redis geospatial indexing
- A powerful aggregations engine
- Supports for all utf-8 encoded text
- Retrieve full documents, selected fields, or only the document IDs
- Sorting results (for example, by creation date)
- Geoshape indexing
- Vector similarity search - KNN, filtered KNN and range query
Cluster support
RediSearch has a distributed cluster version that scales to billions of documents across hundreds of servers. At the moment, distributed RediSearch is available as part of