Last week, we described several criteria to look at to choose a cache. This week, it’s time to list Java cache providers based on these criteria.
- Java Caching System
- Guava
- Caffeine
- Ehcache
- Infinispan
- Coherence Community Edition
- Ignite
- Geode
- Hazelcast
Java Caching System
JCS is a distributed caching system written in Java. It is intended to speed up applications by providing a means to manage cached data of various dynamic natures. Like any caching system, JCS is most useful for high read, low put applications. Latency times drop sharply and bottlenecks move away from the database in an effectively cached system.
Build Embedded Cache Clusters With Quarkus and Red Hat Data Grid
Introduction
There are many ways to configure the cache in a microservices system. As a rule of thumb, you should use caching only in one place; for example, you should not use the cache in both the HTTP and application layers. Distributed caching both increases cloud-native application performance and minimizes the overhead of creating new microservices.
Infinispan is an open-source, in-memory data grid that can run as a distributed cache or a NoSQL datastore. You could use it as a cache, such as for session clustering, or as a data grid in front of the database. Red Hat Data Grid builds on Infinispan with additional features and support for enterprise production environments.
Scalable Data Grid Using Apache Ignite
In this article, I introduce the concept of a Data Grid, it's properties, services it offers, and finally how to design a scalable Data Grid for your needs.
What Is a Data Grid?
A Data Grid is a set of services that delivers a shared data management system, wherein heterogeneous data from various applications and services will be accessible by forming a grid-like structure. This is possible using strong middle-ware applications and services that support data ingress/query from various application requests.