Apache Kafka is a stream-processing platform for storing, consuming, and processing data streams in real-time. In this post, we’ll learn how to produce and consume data using Kafka and Quarkus.

The Apache Software Foundation has released Apache Kafka 3.3.1 with many new features and improvements. In particular, this is the first release that marks KRaft (Kafka Raft) consensus protocol as ...

Originally developed at LinkedIn, Apache Kafka is one of the most mature platforms for event streaming. Kafka is used for high-performance data pipelines, streaming analytics, data integration ...

In late 2014, two creators of Kafka at LinkedIn, Jay Kreps and Neha Narkhede, founded the company Confluent to continue building Kafka and a surrounding ecosystem. In the 11 months immediately ...

Getting the most out of any Apache Kafka event streaming deployment requires a thorough understanding of Kafka consumer groups. Here’s what you need to know.

What are the most important things you learned from building Apache Kafka? This question was originally answered on Quora by Jay Kreps.

Organizations building real-time stream processing systems on Apache Kafka will be able to trust the platform to deliver each messages exactly once when they adopt new Kafka technology planned to be ...

Using Kafka to distributed environment allows overcoming of the memory capacity that cannot be accommodated by one node. In particular, since image data can be stored in the file system, it is ...

Apache Kafka is a key component in data pipeline architectures when it comes to ingesting data. Confluent, the commercial entity behind Kafka, wants to leverage this position to become a platform ...