So in this post I’m going to show an example of what streaming ETL looks like in practice. I’m replacing batch extracts with event streams, and batch transformation with in-flight transformation of these event streams. We’ll take a stream of data from a transactional system built on Oracle, transform it, and stream it into Elasticsearch to land the results to, but your choice of datastore is up to you—with Kafka’s Connect API you can stream the data to almost anywhere! Using KSQL we’ll see how to filter streams of events in real-time from a database, how to join between events from two database tables, and how to create rolling aggregates on this data.
It’s a very useful example.