How Stream Processing Works with ksqlDB

This post provides a deep dive into the internal workings of ksqlDB, explaining how it processes streams of data from Kafka. It details the process of declaring streams with schemas, inserting rows (which are mapped to Kafka records with keys and values), and executing persistent queries. Persistent queries are compiled into Kafka Streams topologies that run as daemons, managing their own processing progression and durably maintaining input partition offsets. The post also covers data transformation, filtering, and rekeying operations, emphasizing how ksqlDB simplifies these complex stream processing tasks by abstracting away low-level details like schema management, serializers, and partitioning strategies.