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.

Distributed systems typically can offer several levels of guaranteed message delivery, including at-least once processing, at-most once processing, and exactly once processing. Current Kafka users ...

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

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 ...

HDFS uses a random-access pattern, which can lead to disk I/O being a bottleneck. Kafka avoids this issue by using sequential access. “Apache Kafka is a distributed messaging system for log processing ...