Confluent Blog

Trains are an excellent source of streaming data—their movements around the network are an unbounded series of events. Using this data, Apache Kafka® and Confluent Platform can provide the foundations

The way in which we handle data and build applications is changing. Technology and development practices have evolved to a point where building systems in isolated silos is somewhat impractical,

One of the most frequent questions and topics that I see come up on community resources such as StackOverflow, the Confluent Platform mailing list, and the Confluent Community Slack group,

In this post I’m going to show what streaming ETL looks like in practice. We’re replacing batch extracts with event streams, and batch transformation with in-flight transformation. But first, a

There has been a lot of talk recently that traditional ETL is dead. In the traditional ETL paradigm, data warehouses were king, ETL jobs were batch-driven, everything talked to everything

In his book Design Patterns Explained, Alan Shalloway compares his car to an umbrella. After all, he uses both to stay dry in the rain. The umbrella has an advantage

This is a guest blog from Alexandra Wang, Software Engineer, Pandora Media. You can connect with her on LinkedIn. Also special thanks to Lawrence Weikum and Stu Thompson as contributors of the work in this post.

Apache Kafka is a high-throughput distributed message system that is being adopted by hundreds of companies to manage their real-time data. Companies use Kafka for many applications (real time stream