Java rate-limiting library based on token-bucket algorithm.

Advantages of Bucket4j

• Implemented on top of ideas of well known algorithm, which are by de-facto standard for rate limiting in the IT industry.
• Effective lock-free implementation, Bucket4j is good scalable for multi-threading case.
• Absolutely non-compromise precision, Bucket4j does not operate with floats or doubles, all calculation are performed in the integer arithmetic, this feature protects end users from calculation errors involved by rounding.
• Ability to switch from one JVM to cluster in two lines of code. Using Bucket4j you are able to limiting something in the cluster of JVMs. Since release 1.2 the Bucket4j supports any GRID solution which compatible with JCache API (JSR 107) specification. Just use your favorite grid including Hazelcast, Ignite, Coherence, Infinispan or any other.
• Ability to specify multiple bandwidths per bucket. For example you can limit 1000 events per hours but not often then 100 events per minute.
• Both synchronous and asynchronous API.
• Pluggable listener API that allows to implement monitoring and logging.
• Ability to use bucket as a scheduler, see examples.

Supported back-ends

As mentioned above in addition to local in-memory buckets, the Bucket4j supports clustered usage scenario on top of following back-ends:

Back-end	Documentation page	Async supported	Optimized serialization
JCache API (JSR 107)	bucket4j-jcache	No	No
Hazelcast	bucket4j-hazelcast	Yes	Yes
Apache Ignite	bucket4j-ignite	Yes	n/a
Inifinispan	bucket4j-infinspan	Yes	Yes
Oracle Coherence	bucket4j-coherence	Yes	Yes

General documentation

Basics:

• Token bucket wikipedia - wikipedia page describes the token-bucket algorithm in classical form.
• Non-formal overview of token-bucket algorithm - the brief overview of token-bucket algorithm.

Examples:

• Basic-usage - examples of basic usage.
• Advanced-usage - examples of advanced usage.
• Asynchronous-usage - examples of asynchronous usage.
• Listening of bucket events - examples of monitoring.

Production checklist

• Common production checklist - Mandatory points that need to be understood before using the Bucket4j in production, independently of local or clustered usage scenarios.
• JCache production checklist - Mandatory points that need to be understood before using the Bucket4j over JCache cluster.

Archive:

• Documentation for legacy releases.

Third-party integrations:

• marcosbarbero/spring-cloud-zuul-ratelimit
• MarcGiffing/Spring Boot Starter for Bucket4j . Demos of usage (incluing Zuul and Hazelcast) can be found there bucket4j-spring-boot-starter-examples.
• JHipster/JHipster API Gateway
• Zivver/Dropwizard Ratelimit

Third-party demos and articles:

• Rate limiting Spring MVC endpoints with bucket4j
• Abdennebi/spring-boot-bucket4j-hazelcast-demo
• ProgrammerSought Bucket4j - preliminary understanding
• Baeldung - Rate Limiting a Spring API Using Bucket4j

Get Bucket4j library

You can add Bucket4j to your project as maven dependency

The Bucket4j is distributed through Maven Central:

<dependency>
    <groupId>com.github.vladimir-bukhtoyarov</groupId>
    <artifactId>bucket4j-core</artifactId>
    <version>6.0.1</version>
</dependency>

You can build Bucket4j from sources

git clone https://github.com/vladimir-bukhtoyarov/bucket4j.git
cd bucket4j
mvn clean install

Have a question?

Feel free to ask via:

• Bucket4j discussions for questions, feature proposals, sharing of experience.
• Bucket4j issue tracker to report a bug.
• Vladimir Bukhtoyarov - Upwork Profile if you want to get one time paid support.

License

Copyright 2015-2020 Vladimir Bukhtoyarov Licensed under the Apache Software License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0.