Roundup December 2021
Roundup December 2021... Read More
Hop is entirely metadata driven. Every object type in Hop describes how data is read, manipulated or written, or how workflows and pipelines need to be orchestrated.
Metadata is what drives Hop internally as well. Hop uses a kernel architecture with a robust engine. Plugins add functionality to the engine through their own metadata.
Hop workflows and pipelines are definitions of how data needs to be processed.
Once designed, a pipeline can be executed on any supported runtime. Hop has built-in support to run pipelines locally and remotely in the native Hop runtime, or on Apache Spark, Apache Flink or Google Dataflow through the Apache Beam runtimes.
Hop workflows and pipelines are developed visually through an intuitive drag and drop interface.
Visual development allows data developers and data engineers to keep focus on the business logic that needs to be implemented, on what needs to be done instead of how it needs to be done.
Managing, testing and deploying workflows and pipelines can be a daunting task.
Developers and engineers can manage the entire project life cycle from the Hop Gui: switch between projects, environments, runtime configurations, manage git versions etc.
Hop is your project!