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 ...
Real-time stream processing architectures differ significantly from batch processing: whereas batch processing requires massive amounts of storage and CPU and memory resources sufficient to churn ...
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, Inc., the data streaming pioneer, is introducing new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making. Snapshot queries, ...
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 ...
When stream processors began, they were considered by the computing industry as a mere addition to the batch data stack or other stacks being utilized by information technology administrators. But ...
Streaming data records are typically small, measured in mere kilobytes, but the stream often goes on and on without ever stopping. Streaming data, also called event stream processing, is usually ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results