With Hazelcast, we are dealing more with a technology than a server product, a library to build a system around rather than retrospectively bolting it on, 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 it and alongside it.

With such a large range of generic capabilities, there is an entire world of problems that Hazelcast can help solve. We can use the technology in many ways; 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 away from monolithic systems to such a generic scalable one, there is no limit to the performance we can unlock.

This will allow us to keep our application and data layers separate, but enabling the ability to scale them up independently as our application grows. This will avoid our application becoming a victim of its own success, while hopefully taking the world by storm.

In the next chapter, we shall start using the technology itself and investigate the data collections we have just discovered.