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

Streaming data platform Kafka uses a “publish-and-subscribe” model that links data sources to data receivers to enable constant and distributed monitoring.

Real-time data streaming with Apache Kafka is very efficient as it enables integration and in-stream analytics on the data as it moves through the stream. It’s clear that CDC is seen as the optimal ...

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 ...

Hortonworks Inc. today added improved support for Apache Kafka to its Hortonworks DataPlane Service, underlining the growing importance of streaming sources to its big-data customers. Launched ...

Unlike traditional enterprise messaging software, Kafka is able to handle all the data flowing through a company, and do it in near real time. This is desperately needed as data volumes skyrocket.

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.

Kafka is a widely-used open-source project that allows companies to analyze and process streams of data, used in applications such messaging apps or infrastructure monitoring tools.

Learn More Aiven, a cloud-data platform based in Helsinki, has fleshed out an open-source ecosystem for Apache Kafka, a popular event-streaming platform.