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I'm one of the authors of Kafka. I've outlined some differences between Flink's support for streaming SQL and KSQL in this Twitter thread - https://twitter.com/juliusvolz/status/902283513382051840

Here's a summary: - KSQL has a completely Interactive SQL interface, so you don't have to switch between DSL code and SQL.

- KSQL upports local, distributed and embedded modes. Is tightly integrated with Kafka's Streams API and Kafka itself; doesn't reinvent the wheel. So is simple to use and deploy.

- KSQL doesn't have external dependencies, for orchestration, deployment etc.

- KSQL has native support for Kafka's exactly once processing semantics, supports and stream-table joins.

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- Flink as a whole (and SQL sits just on the DataStream API) works local, distributed and embedded as well. - Flink does not have any external dependencies, not even Kafka/ZooKeeper; it is self-contained. One can even just receive a data stream via a socket if that works for the use case. - Flink itself has always had exactly-once semantics, and works also exactly-once with Kafka.