Stream processing systems are pivotal to modern data-driven environments, enabling the continual ingestion, processing and analysis of unbounded data streams across distributed computing resources.

Today, the way companies are leveraging data has changed. The world has moved from static stores held in databases to adding dynamic and event-driven data in flight. The driver of this dynamic is ...

We live in a world in motion. Stream processing allows us to record events in the real world so that we can take action or make predictions that will drive better business outcomes. The real world is ...

Confluent CEO Jay Kreps argues that data stored in warehouses or lakehouses aren’t appropriate for the reliable and well-governed AI agents. Confluent CEO Jay Kreps took to the stage at the vendor’s ...

The ability to move, manage and process data in real time is the domain of data streaming, which is largely dominated by a series of open-source technologies. The ability to stream data is a core ...

Confluent has unveiled new capabilities that unite batch and stream processing to enable more effective AI applications and agents. The aim? Confluent wants to position itself as an essential platform ...

Attention business leaders: We’ve just reached another inflection point of how data can be used to drive better business results. This is the era of streaming data. The Internet giants have ...

The de facto standard for real-time stream processing is sometimes described as being complex and difficult to learn. Start by understanding these core principles. In recent years, Apache Flink has ...