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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.
Event design plays a big role in your ability to fix bad data in your streams. But if you’ve wrecked a stream with bad data (i.e., it’s unavoidably contaminated), you'll need to employ a "rewind, rebuild, and retry" strategy.
In this edition, we’ll have a look at creating Kafka Streams topologies—exploring the dependency injection and design principles with Spring Framework, while also highlighting some syntactic sugar of Kotlin that makes for more concise and legible topologies.
This blog post talks about Confluent’s newest enhancement to their fully managed connectors: the ability to assume IAM roles.
At a high level, bad data is data that doesn’t conform to what is expected, and it can cause serious issues and outages for all downstream data users. This blog looks at how bad data may come to be, and how we can deal with it when it comes to event streams.
The blog post provides a comprehensive overview of the Flink Table API, demonstrating how it enables developers to express complex data processing logic using Java or Python in a user-friendly manner. It also includes practical examples and guidance, making it a valuable resource for anyone...
Read our latest Confluent Champion post to learn what motivated Nadine Capelle, staff solutions architect in Professional Services, to join the world of data streaming.