RedisBloom: Probabilistic Data Structures for Redis

[!NOTE] Starting with Redis 8, all RedisBloom data structures are integral to Redis. You don't need to install this module separately.

We no longer release standalone versions of RedisBloom.

See https://github.com/redis/redis

Overview

RedisBloom adds a set of probabilistic data structures to Redis, including Bloom filter, Cuckoo filter, Count-min sketch, Top-K, and t-digest. Using this capability, you can query streaming data without needing to store all the elements of the stream. Probabilistic data structures each answer the following questions:

• Bloom filter and Cuckoo filter:
  • Did value v already appear in the data stream?
• Count-min sketch:
  • How many times did value v appear in the data stream?
• Top-k:
  • What are the k most frequent values in the data stream?
• t-digest:
  • Which fraction of the values in the data stream are smaller than a given value?
  • How many values in the data stream are smaller than a given value?
  • Which value is smaller than p percent of the values in the data stream? (What is the p-percentile value?)
  • What is the mean value between the p1-percentile value and the p2-percentile value?
  • What is the value of the nᵗʰ smallest/largest value in the data stream? (What is the value with [reverse] rank n?)

Answering each of these questions accurately can require a huge amount of memory, but you can lower the memory requirements drastically at the cost of reduced accuracy. Each of these data structures allows you to set a controllable trade-off between accuracy and memory consumption. In addition to having a smaller memory footprint, probabilistic data structures are generally much faster than accurate algorithms.

Documentation

https://redis.io/docs/latest/develop/data-types/probabilistic/

License

Starting with Redis 8, RedisBloom is licensed under your choice of: (i) Redis Source Available License 2.0 (RSALv2); (ii) the Server Side Public License v1 (SSPLv1); or (iii) the GNU Affero General Public License version 3 (AGPLv3). Please review the license folder for the full license terms and conditions. Prior versions remain subject to (i) and (ii).

Code contributions

By contributing code to this Redis module in any form, including sending a pull request via GitHub, a code fragment or patch via private email or public discussion groups, you agree to release your code under the terms of the Redis Software Grant and Contributor License Agreement. Please see the CONTRIBUTING.md file in this source distribution for more information. For security bugs and vulnerabilities, please see SECURITY.md.