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	Thin-client support
`JCache API (JSR 107)`	bucket4j-jcache	No	No	No
`Hazelcast`	bucket4j-hazelcast	Yes	Yes	Planned
`Apache Ignite`	bucket4j-ignite	Yes	n/a	Yes
`Inifinispan`	bucket4j-infinspan	Yes	Yes	No
`Oracle Coherence`	bucket4j-coherence	Yes	Yes	No

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.

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:

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>6.2.0</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.

tr7zw/bucket4j