A couple of years have passed since we last looked into in-memory caches here at ConSol. In that time a bunch of things have happened:
Probably the most significant thing that happened was that the oldest Java Service Request JSR 107, also known as JCache, finally reached ‘Release’ status. This JSR was a long time in the making taking a whole 13 years since the initial proposal back in 2001.
The existing In-memory caches providers, like Hazelcast, have received a whole host of new features including things like support for distributed transactions, a new Map-Reduce API, interceptors for executing business logic, when the cache entries change, to mention just a few.
Distributed caches have evolved into an independent branch of Big Data solutions: When it comes to fast read and write access, distributed caches are the solution of choice.
Dr. Fabian Stäber gave a talk a JayDay 2013 where he introduced and compared the leading distributed cache implementations:
Based on a simple example application, the basic functionality is presented, and the specific strengths and weaknesses of the different cache architectures are highlighted and compared.