Learn how data fabrics — scalable data architectures that can handle all OT and IT data types, historize them and make the ...

But Dataflow is a little different in that Google is offering it solely as a cloud service, something that anyone can access over the internet.

Significantly, Google Cloud Dataflow is meant to replace MapReduce, the software at the heart of Hadoop and other big data processing systems. MapReduce was originally developed by Google and ...

Google announced Cloud Dataflow last June as a managed service designed to help companies ingest and analyze huge data sets both in batch processing and in real-time streaming mode.

Along with new features for its Google BigQuery cloud analytics platform, the company's Cloud Dataflow managed data-processing service is now available in beta.

With Cloud Dataflow — in its ideal state — data analysts will be able use the same system for creating their pipelines, no matter the underlying architecture they want to run them on.

Google expanded its Cloud Platform today with a new managed service called Cloud Dataflow that creates data pipelines that can ingest, transform and analyze data. Developers can use the service to ...

In a simple batch processing test, Google Cloud Dataflow beat Apache Spark by a factor of two or more, depending on cluster size ...

“Cloudera DataFlow automates and manages cloud-native data flows on Kubernetes – and it is something only we offer,” said Dinesh Chandrasekhar, Head of Product Marketing, Data-in-Motion at Cloudera.

Developers get one more platform for running Dataflow pipelines. They can now run their programs on the Apache Flink distributed processing engine.