Jean-Sebastien Brunner gives us some use cases:
In Part One of our “Inside Flink” blog series, we explored the critical role of stream processing and why developers are increasingly choosing Apache Flink® over other frameworks.
In this second installment, we’ll showcase how innovative teams across every industry and size are putting stream processing into practice – from streaming data pipelines to train ML models or more timely analytics to fraud detection in finance and real-time inventory management in retail. We’ll also discuss how Flink is uniquely suited to support a wide spectrum of use cases and helps teams uncover immediate insights in their data streams and react to events in real time.
This article stays more at the “art of the possible” level rather than drilling into how we can do it.