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.

Confluent, a leader in data streaming and steward of the open-source Apache Kafka system, recently announced its new "Data Streaming for AI" initiative to aid organizations in developing real-time AI ...

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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 ...

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 ...

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 ...

Streaming data observability startup Datorios Ltd. today announced the immediate availability of a new real-time observability platform for the big-data processing framework Apache Flink. With the new ...

Confluent is positioning itself as the "context layer for enterprise AI" with new capabilities that aim to solve the problem plaguing generative AI investments—lack of fresh, trustworthy data—by ...

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 ...