I understand the underlying architecture is fundamentally different, but the end result seems kind of akin to some of the "complex event processing" (CEP) tools out there like Esper (ie. feeding incoming data into established queries instead of executing queries against at-rest data). Would this fit similar sorts of use cases / fit into the CEP market?
Yes KSQL is ideal for use cases similar to those that CEP was initially targeted for and more - from real-time anomaly detection, monitoring, analytics to application development and Streaming ETL. As you alluded to, the big difference is that KSQL is designed as a distributed Streaming SQL engine that can run at Kafka scale.
