The Apache Kafka phenomenon reached a new high today when Confluent announced a $50 million investment from the venture capital firm Sequoia. The investment signals renewed confidence that Kafka is ...

Apache Kafka is a strong choice to handle real-time data streaming as it ingests, persists and presents streams of data for consumption and use by individuals for analytics. Basically, Kafka operates ...

Apache Kafka continues its ascent as attention shifts from lumbering Hadoop and data lakes to real-time streams ...

When Confluent launched a cloud service in 2017, it was trying to reduce some of the complexity related to running a Kafka streaming data application.

In this article, author Robin Moffatt shows how to use Apache Kafka and KSQL to build data integration and processing applications with the help of an e-commerce sample application.

Confluent Inc. today announced new features in its cloud service that make it easier for users of its Apache Kafka-based streaming engine to store data in the Apache Iceberg table format. The new ...

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.

Because Kafka is associated with data in motion, it is often confused with streaming engines. But Kafka acts as traffic cop, serving as ingest point from a stream, or transmission point to a stream.

Life happens as a continuous flow of events (a stream). Ted Dunning and Ellen Friedman describe new designs for streaming data architecture that help you get real-time insights and greatly improve ...

The insurance group is using Kafka’s data streaming capabilities to integrate disparate data sources and provide real-time data services to support its business.