This article explains why local caches are essential in high‑performance services, outlines required cache features, compares four Java‑based local cache implementations (ConcurrentHashMap, Guava Cache, Caffeine, Ehcache), and offers practical solutions for consistency, hit‑rate improvement, and technology selection.
This guide explains MyBatis's two‑level caching mechanism, shows how to use the default first‑level cache and manually enable the second‑level cache in a Spring Boot project, includes code examples, test cases, third‑party Ehcache integration, and key considerations for safe deployment.
This article explains why a first‑level local cache is essential for high‑performance services, outlines required cache features, compares four Java implementations (ConcurrentHashMap, Guava, Caffeine, Encache), and provides solutions for consistency, hit‑rate improvement, and technology selection, concluding that Caffeine offers the best performance.
This article explains the role of local in‑memory caches in high‑performance service architectures, compares implementations such as ConcurrentHashMap, Guava Cache, Caffeine, and Ehcache, discusses cache consistency and hit‑rate challenges, and recommends Caffeine as the preferred solution for multi‑level caching with Redis or Memcached.
An overview of two‑level caching architecture, the motivations for using local in‑memory caches, essential features of a local cache, comparative analysis of implementations using ConcurrentHashMap, Guava Cache, Caffeine, and Ehcache, and strategies for consistency, hit‑rate improvement, and practical code examples.
This article introduces Ehcache, an open‑source Java local‑cache framework, explains its layered storage options, flexible expiration policies, eviction strategies, and provides comprehensive code examples for configuring in‑memory, off‑heap, and disk‑persistent caches, along with practical usage tips and performance considerations.
This article reviews three popular Java in‑process caching libraries—Guava, Caffeine, and Ehcache—explaining their configuration options, performance characteristics, monitoring capabilities, advantages and disadvantages, and provides a side‑by‑side comparison to help developers choose the most suitable local cache for their applications.
An in‑depth comparison of popular Java in‑process caching solutions—Guava, Caffeine, and Ehcache—covers their expiration policies, capacity limits, eviction strategies, monitoring features, performance optimizations, and ideal use cases, helping developers select the most suitable cache for their applications.
This tutorial explains how to enable and use Spring Cache with annotations like @Cacheable, @CacheEvict, and @CachePut, integrates JSR‑107 and Ehcache, provides full Maven and configuration examples, and demonstrates caching behavior through a series of practical code snippets and tests.
Learn how to enable and configure transparent caching in Spring Boot 2.3 using JSR‑107 annotations and Ehcache, covering annotation usage, custom key generators, service and controller implementation, Maven dependencies, YAML and XML settings, and practical testing of cache put, get, and removal operations.
An overview of two-level cache architecture explains why local in-memory caches are needed, outlines essential cache features, compares implementations using ConcurrentHashMap, Guava Cache, Caffeine, and Ehcache with code examples, and discusses consistency, hit-rate improvement, and technology selection, recommending Caffeine for best performance.
This article explains MyBatis caching fundamentals, detailing first- and second-level cache concepts, configuration, cache invalidation scenarios, and custom cache integration with EHCache, supplemented by practical code snippets and quiz questions to illustrate cache behavior across SqlSessions.
With hardware costs dropping, many default to Redis for caching, but it isn’t always optimal; this article examines EhCache—a pure‑Java, in‑process cache—covering its architecture, eviction policies, API and XML configurations, and step‑by‑step Spring Boot integration, helping you decide when to prefer it.
This article provides a comprehensive overview of caching in large distributed systems, covering theory, common components, classification, CDN and reverse‑proxy caches, local application caches, popular implementations like Ehcache, Guava, Memcached and Redis, and a detailed comparison of their features and trade‑offs.
This article introduces Spring Cache as a unified caching solution that abstracts away the specifics of Redis, Ehcache, and other providers, explains its core concepts, annotations, configuration, and demonstrates practical usage with code examples to eliminate manual cache handling.
This article introduces Spring Cache as a framework‑agnostic caching abstraction that eliminates manual cache code, explains its core concepts, annotations, configuration options, and demonstrates practical usage with Redis and custom key, condition, and eviction strategies in Spring Boot applications.
This tutorial explains how to integrate Ehcache into a Spring Boot application, covering Maven dependencies, YAML and XML configuration, enabling caching with @EnableCaching, using cache annotations, and manually operating caches via CacheManager, complete with code examples.
This article provides a comprehensive overview of Ehcache, covering its core components, data‑flow mechanisms, XML configuration options, persistence behavior, and key features such as multi‑level storage, monitoring interfaces, and cache‑manager scalability for Java applications.
This tutorial explains why in‑process caches like EhCache can cause consistency problems in clustered environments and demonstrates step‑by‑step how to replace EhCache with Redis in a Spring Boot 2.x application, including dependency setup, configuration, and a unit test that verifies caching behavior.
This tutorial explains how to configure EhCache for distributed caching in a Spring Boot application, covering serialization, XML cluster settings, deployment parameters, REST endpoints for testing, and strategies to keep cache data consistent across multiple JVM instances.
This article explains how Spring Boot automatically detects cache providers, shows how to replace the default ConcurrentHashMap with EhCache by adding the dependency, configuring ehcache.xml, and verifying the CacheManager type through unit tests, providing complete code examples and step‑by‑step instructions.
This article explains Apache Shiro's security architecture, demonstrates how to create authentication tokens, configure realms, use caching and hashing for password protection, and integrate Shiro with Spring MVC through XML and Java code examples.
This article provides a comprehensive overview of caching in large distributed systems, covering CDN, reverse‑proxy, local and distributed caches, popular implementations such as Ehcache, Guava, Memcached and Redis, common pitfalls like consistency and avalanche, and practical solutions with real‑world case studies.
This article explains how a three‑layer caching architecture—combining Nginx, Redis, and Ehcache—along with template engines, double‑Nginx routing, persistence mechanisms, cluster setups, and various cache‑update strategies can dramatically improve hit rates, reduce database pressure, and prevent cache‑related failures in high‑traffic applications.
This article explains various cache eviction strategies, compares heap, off‑heap, disk and distributed cache types, and provides concrete Java implementations using Guava Cache, EhCache 3.x and MapDB with code examples and usage patterns such as Cache‑Aside and Cache‑As‑SoR.
This article explains the concept of caching in Java, the importance of reducing database I/O, introduces Spring Cache annotations and their limitations, demonstrates conditional caching with code examples, and provides configuration details for integrating Ehcache and Redis as cache providers.
This article examines how popular caching systems such as Redis, Memcached, Guava Cache, and Ehcache implement eviction policies like LRU, LFU, and FIFO, comparing their algorithmic approaches, code implementations, and expiration handling mechanisms.
