Not the one to be behind the times, Hazelcast provides us with a power batch analytical engine to find, transform, and extract information from data. Based on a popular and scalable framework, the shear flexibility of this interface opens up a whole world of data problems to solve. It also provides a capability that is traditionally overlooked in modern data storage systems—aggregation. Whilst we have been given the ability, it is important to remember that traversing an entire dataset to perform reductions or aggregations even whilst distributed and the load shared will be a relatively intense task for the cluster and there were be no substitute for key-based access. That being said, if used in the right place and at the right time, it is a very powerful feature to have at our application's disposal.

In the next chapter, we will examine the different architectural setups that Hazelcast can operate in, the situations that suit the various options, and how to use them.