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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Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Data runs business. We’ve been told this now immutable ...

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 ...

Discover how ISVs are moving beyond batch processing to build high-margin, real-time data streaming features in their software.

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 ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

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 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 ...