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RedisBloom: Probabilistic Data Structures for Redis

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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.

RedisBloom is part of Redis Stack.

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You can either get RedisBloom setup in a Docker container or on your own machine.


To quickly try out RedisBloom, launch an instance using docker:

docker run -p 6379:6379 -it --rm redis/redis-stack-server:latest

Build it yourself

You can also build RedisBloom on your own machine. Major Linux distributions as well as macOS are supported.

First step is to have Redis installed, of course. The following, for example, builds Redis on a clean Ubuntu docker image (docker pull ubuntu):

mkdir ~/Redis
cd ~/Redis
apt-get update -y && apt-get upgrade -y
apt-get install -y wget make pkg-config build-essential
tar -xzvf redis-stable.tar.gz
cd redis-stable
make distclean
make install

Next, you should get the RedisBloom repository from git and build it:

apt-get install -y git
cd ~/Redis
git clone --recursive
cd RedisBloom
bash -l

Then exit to exit bash.

Note: to get a specific version of RedisBloom, e.g. 2.4.5, add -b v2.4.5 to the git clone command above.

Next, run make run -n and copy the full path of the RedisBloom executable (e.g., /root/Redis/RedisBloom/bin/linux-x64-release/

Next, add RedisBloom module to redis.conf, so Redis will load when started:

apt-get install -y vim
cd ~/Redis/redis-stable
vim redis.conf

Add: loadmodule /root/Redis/RedisBloom/bin/linux-x64-release/ under the MODULES section (use the full path copied above).

Save and exit vim (ESC :wq ENTER)

For more information about modules, go to the Redis official documentation.


Run redis-server in the background and then redis-cli:

cd ~/Redis/redis-stable
redis-server redis.conf &

Give it a try

After you setup RedisBloom, you can interact with it using redis-cli.

Create a new bloom filter by adding a new item:

#> BF.ADD newFilter foo
(integer) 1

Find out whether an item exists in the filter:

#> BF.EXISTS newFilter foo
(integer) 1

In this case, 1 means that the foo is most likely in the set represented by newFilter. But recall that false positives are possible with Bloom filters.

#> BF.EXISTS newFilter bar
(integer) 0

A value 0 means that bar is definitely not in the set. Bloom filters do not allow for false negatives.

Client libraries

Project Language License Author Stars Package Comment
jedis Java MIT Redis Stars Maven
redis-py Python MIT Redis Stars pypi
node-redis Node.JS MIT Redis Stars npm
nredisstack .NET MIT Redis Stars nuget
redisbloom-go Go BSD Redis Stars GitHub
rueidis Go Apache License 2.0 Rueian Stars GitHub
rebloom JavaScript MIT Albert Team Stars GitHub
phpredis-bloom PHP MIT Rafa Campoy Stars GitHub
phpRebloom PHP MIT Alessandro Balasco Stars GitHub
vertx-redis-client Java Apache License 2.0 Eclipse Vert.x Stars GitHub
rustis Rust MIT Dahomey Technologies Stars GitHub


Documentation and full command reference at

Mailing List / Forum

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


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