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.

Data can be likened to a stream of water when a large amount of data is generated continuously. A variety of data including applications, networked devices, server log files, various online activities ...

Modern enterprises are hitting scale (>100 million users) at an unprecedented rate. Building applications to retrospectively meet this scale is no longer an option. And scale isn’t just limited to end ...

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 ...

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 ...

On Confluent Cloud for Apache Flink®, snapshot queries combine batch and stream processing to enable AI apps and agents to act on past and present data New private networking and security features ...