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.

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 ...

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 ...

New features include a Real-time Context Engine for GenAI Agents and MCP Server—uniting AI-assisted pipelines, unified orchestration, cost optimization, and observability in a single serverless ...

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 ...

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Learn how to use advanced techniques like short-circuiting, parallel execution, virtual threads, and stream gatherers to maximize Java stream performance. My recent Java Stream API tutorial introduced ...