Cloud Native Scalable Rule Engine Demo


The distributed compute features of Hazelcast (such as Executors, EntryProcessors, and Jet pipelines) provide powerful capabilities for building distributed applications. By moving business logic into the in-memory data grid, movement of data across the network is minimized; this results in higher throughput and lower latency. Applications in this way can easily scale up and out given the built-in threading model and elastic scaling features of Hazelcast.

In this video, an application for fraud detection for credit card transactions is demonstrated, which is built on top of a reusable, generic rule engine implementation that is freely available online as an example implementation of several of Hazelcast’s key distributed computation capabilities.