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 release of Kafka 0.9, its commercial counterpart Confluent Platform 2.0, and new distro component MapR Streams, bring prominence and maturity to streaming data processing in the Hadoop ecosystem.

At the heart of an effective stream-based architecture is the right message-passing technology. An emerging class of message-passing software, including Apache Kafka and MapR Streams, supports ...

By hooking Kafka APIs into the Vast Data Platform, you don’t have to buy a bunch of X86 servers, each with their own local storage and needing to replicate and synchronize data using brokers that talk ...

Confluent Platform 3.0 ships, with a GA release of Kafka Streams. And Confluent Enterprise now includes a new commercial tool: Confluent Control Center.

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 ...

At the Kafka Summit, Confluent unveils enhanced functionalities aimed at streamlining AI and stream processing workflows.