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RedisBloom - Probabilistic Datatypes Module for Redis

RedisBloom module provides four datatypes, a Scalable Bloom Filter and Cuckoo Filter, a Count-Mins-Sketch and a Top-K. Bloom and Cuckoo filters are used to determine (with a given degree of certainty) whether an item is present or absent from a collection. While Count-Min Sketch is used to approximate count of items in sub-linear space and Top-K maintains a list of K most frequent items.

Quick Start Guide

  1. Quick Start
  2. Command references
  3. Client libraries
  4. References
  5. License

Command references

Detailed command references for each data structure:

Bloom vs. Cuckoo

Bloom Filters typically exhibit better performance and scalability when inserting items (so if you're often adding items to your dataset then Bloom may be ideal), whereas Cuckoo Filters are quicker on check operations and also allow deletions.

Client libraries

Each driver comes with its own documentation in the Readme of the driver repo.

Project Language License Author URL
redisbloom-py Python BSD Redis Labs GitHub
JReBloom Java BSD Redis Labs GitHub
rebloom JavaScript MIT Albert Team GitHub

References

Webinars

  1. Probabilistic Data Structures - The most useful thing in Redis you probably aren't use

Past blog posts

  1. ReBloom Quick Start Tutorial
  2. Developing with Bloom Filters
  3. ReBloom – Bloom Filter Datatype for Redis + Benchmark
  4. Meet Top-K: an Awesome Probabilistic Addition to RedisBloom

Mailing List / Forum

Got questions? Feel free to ask at the RedisBloom mailing list.

License

Redis Source Available License Agreement - see LICENSE