Data stream processing is defined as a system performing transformations for creating analytics on data inside a stream. In Part 1 of this series, we defined data streaming to provide an understanding ...

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 ...

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 ...

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.

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.

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

Yet almost all modern data streaming stacks are built on-top of Apache Kafka, which was designed in 2011 to run in static data centers.

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.

A data streaming solution must account for speed, security, scaling and more if it’s to provide the productivity, service and information it’s designed to deliver.

WarpStream Labs, the cloud native data streaming infrastructure company, announced it raised $20M in funding led by Greylock and Amplify Partners. Ang ...