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 ...

Cloud-native streaming database startup RisingWave Labs Ltd. said today it has closed on a $36 million round of funding that brings its total amount raised to date to more than $40 million. Today’s ...

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 ...

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 ...

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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 ...

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 ...