[Workshop] Stream-Verarbeitung leicht gemacht mit Flink | Jetzt registrieren
Change data capture is a popular method to connect database tables to data streams, but it comes with drawbacks. The next evolution of the CDC pattern, first-class data products, provide resilient pipelines that support both real-time and batch processing while isolating upstream systems...
Learn how the latest innovations in Kora enable us to introduce new Confluent Cloud Freight clusters, which can save you up to 90% at GBps+ scale. Confluent Cloud Freight clusters are now available in Early Access.
Learn how to contribute to open source Apache Kafka by writing Kafka Improvement Proposals (KIPs) that solve problems and add features! Read on for real examples.
Apache Flink can be used for multiple stream processing use cases. In this post we show how developers can use Flink to build real-time applications, run analytical workloads or build real-time pipelines.
Learn why stream processing is such a critical component of the data streaming stack, why developers are choosing Apache Flink as their stream processing framework of choice, and how to use Flink with Kafka.