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Caffeine project preview
Developer ToolsAlternative to EhcacheAlternative to Guava CacheAlternative to Redis

Caffeine

A high performance, near optimal caching library for Java 8+ using Window TinyLFU.

View on GitHub
LicenseApache-2.0
GitHub stars14.5k
Last commit6 days ago
Tags5 topics
Tinylfu Cache JavaCaffeine CacheHigh Throughput Memory CacheNear Optimal CachingDeveloper Tools
Overview

Why consider Caffeine?

Caffeine is an open-source, high-performance in-memory caching library for Java written by Ben Manes. Powered by the Window TinyLFU eviction algorithm, Caffeine delivers near-optimal hit ratios and nanosecond read/write concurrency for high-throughput enterprise systems.

Guided learning

Learn Caffeine by building

Practical setup notes, real use cases, and copy-ready examples in one focused guide.

1 min read 2 sections
In this guide2 sections

Overview of Caffeine

Caffeine provides concurrent in-memory caching with automatic frequency-based eviction.

Quickstart

xml
1<dependency>
2 <groupId>com.github.ben-manes.caffeine</groupId>
3 <artifactId>caffeine</artifactId>
4 <version>3.1.8</version>
5</dependency>

Caffeine is licensed under the Apache License Version 2.0.

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Caffeine FAQs

Caffeine is listed as a Developer Tools tool on TiloBox. Review the overview, features, and official documentation on this page to decide whether it solves your specific workflow.

Start with the project's GitHub repository for supported installation and deployment instructions. Test the setup with representative data or a small project before rolling it out more widely.

Caffeine is listed under the Apache-2.0 license. Read the complete license text and the project's notices before using, modifying, or distributing the software.

Production readiness depends on your requirements. Review maintenance activity, security practices, documentation, backup and upgrade procedures, and compatibility with your stack; then validate it in a non-production environment.

Caffeine is listed as an alternative to Ehcache. Compare the core workflow, deployment model, integrations, and licensing against your must-have requirements before switching.