Do you think that analytics are run on stored data sets? Think again, the combination of Apache Kafka and Stream Processing enables analytics on real-time data streams.
First, we give a brief overview of stream processing and how it differs from the request response model of analytics on stored data. Next, we cover the characteristics of Kafka which make it such a good fit for Stream processing and why they matter. Finally, we show a number of use cases which highlight how stream processing is being used to do real-time analytics at scale with very low latency.
|Mike Spicer, Senior Technical Staff Member and Chief Architect, IBM and IBM Streams|