Today’s the tools, architectures, and approaches all are very different from those used historically for data integration and data warehousing, which grew up during an era of batch processing.

Apache Beam, a unified programming model for both batch and streaming data, has graduated from the Apache Incubator to become a top-level Apache project. Aside from becoming another full-fledged ...

Apache Storm Apache Storm is a distributed stream processing framework that was created by Nathan Marz about a decade ago to provide a more elegant way to process large amounts of incoming data. Storm ...

International Data Corp. has forecast that the stream processing market will grow at a compound annual growth rate of 21.5% through 2028, driven by increased data velocity, real-time analytics and ...

Instead of managing complex pipelines for a sprawling infrastructure of different components, with the streaming data warehouse, data engineers can perform all of their preparation and processing ...

Confluent, Inc. (Nasdaq: CFLT), the data streaming pioneer, announced new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making.

The Lambda Architecture Dream Lambda architecture has been heralded as a savior for handling both batch and stream processing, offering a way to balance speed and accuracy. It sounded like the ...

The world of stream processing grew up around these ideas – and when people still thought that batch processing was more efficient Kreps said that he always thought that was a strange idea to ...

Data streaming, for the uninitiated, is all about harnessing and processing data with millisecond latency from myriad sources as it’s generated — this can be useful if a company wants insights ...

The batch processing feature is suitable for OEMs and end users with thermal processes who seek to collect manufacturing part processing thermal data, simplifying and automating data record entry and ...