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

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 ...

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 ...

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

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.

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 ...

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. (NASDAQ: CFLT) is a leading data streaming platform provider. Data streaming is the continuous transmission of ...

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.

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.