Summary

With Hazelcast, we are dealing more with a technology than a server product; it is a distributed core library to build a system around rather than trying to retrospectively bolt on distribution, or blindly connecting to an off-the-shelf commercial system. While it is possible (and in some simple cases, quite practical) to run Hazelcast as a separate server-like cluster and connect to it remotely from our application, some of the greatest benefits come when we develop our own classes and tasks run within and alongside it.

With such a large range of generic capabilities, there is an entire world of problems that Hazelcast can help us solve. We can use the technology in many ways. We can use it in isolation to hold data such as user sessions, run it alongside a more long-term persistent data store to increase capacity, or shift towards performing high performance and scalable operations on our data. By moving more and more responsibility from monolithic systems to such a generic, scalable one, there is no limit to the performance that we can unlock.

This technology not only helps us to keep the application and data layers separate, but also enables us to scale them up independently as our application grows. This will prevent our application from becoming a victim of its own success while taking the world by storm.

In the next chapter, we shall start using the technology and investigate the data collections that we discovered in this chapter.