Streaming data, simplified: Kafka Streams reaches GA


Wouldn't it be great if working with streaming data were just as simple as working with data at rest? And imagine if the two could be modeled, processed and coded against similarly; that would let organizations working with analytics broaden the scope of their work to do real-time streaming analytics too. We're not quite there yet, but Kafka Streams, a lightweight Java library that works with the Apache Kafka stream data platform, gets us closer, by empowering mainstream Java developers. And today, with the release of Confluent Data Platform 3.0, Kafka Streams has reached general availability (it had been released in preview form in Confluent Data Platform 2.0). How it works; where it's useful At the risk of oversimplifying things, Kafka Streams makes streaming data look like a conventional table, of keys and value pairs (the data structure is called a KTable).

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