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

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RediSearch

Querying, secondary indexing, and full-text search for Redis

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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.

The fastest way to get up and running with RediSearch is by using the Redis Stack Docker image.

Trying RediSearch

To try RediSearch, either use the RediSearch Docker image, or create a free Redis Cloud Essentials account to get a RediSearch instance in the cloud.

Docker image

The Redis Stack Docker image makes it easy to try RediSearch.

To create a local RediSearch container, run:

$ docker run -p 6379:6379 redis/redis-stack-server:latest

To connect to this instance, run:

$ redis-cli

Documentation

The RediSearch documentation provides a complete overview of RediSearch. Helpful sections include:

Mailing list and forum

Got questions? Join us in #redisearch on the Redis Discord server.

If you have a more detailed question, drop us a line on the RediSearch Discussion Forum.

Client libraries

You can use any standard Redis client library to run RediSearch commands, but it's easiest to use a library that wraps the RediSearch API.

Project Language License Author Stars Comment
jedis Java MIT Redis Stars
redisson Java MIT Redisson Stars
redis-py Python MIT Redis Stars
node-redis Node.js MIT Redis Stars
nredisstack .NET MIT Redis Stars
redis-om Python BSD Redis redis-om-python-stars
lettusearch Java Apache 2.0 Redis lettusearch-stars
spring-redisearch Java Apache 2.0 Redis spring-redisearch-stars
redis-om-spring Java BSD Redis redis-om-spring-stars
redisearch-go Go BSD Redis redisearch-go-stars
rueidis Go Apache 2.0 Rueian rueidis-stars
Redis-om JavaScript BSD Redis redis-om-node-stars
Redis.OM .NET BSD Redis redis-om-dotnet-stars
redisearch-php PHP MIT Ethan Hann redisearch-php-stars
php-redisearch PHP MIT MacFJA MIT php-redisearch-stars
redisearch-api-rs Rust BSD Redis redisearch-api-rs-stars
redi_search_rails Ruby MIT Dmitry Polyakovsky redi_search_rails-stars
redisearch-rb Ruby MIT Victor Ruiz redisearch-rb-stars
redi_search Ruby MIT Nick Pezza redi_search-stars

RediSearch features

  • Full-Text indexing of multiple fields in Redis hashes
  • Incremental indexing without performance loss
  • Document ranking (using tf-idf, with optional user-provided weights)
  • 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)

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 Redis Enterprise Cloud and Redis Enterprise Software.

See RediSearch on Redis Enterprise for more information.

License

RediSearch is licensed under the Redis Source Available License 2.0 (RSALv2) or the Server Side Public License v1 (SSPLv1).

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

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