Syncsort Enhances its DMX-h Platform with Spark 2.0 Support

Syncsort is making advancements in its big data integration solution, DMX-h, that help organizations to accelerate their business objectives by speeding development, adapting to evolving data management requirements, and taking advantage of the rapid innovation in big data technology. The platform update introduces new integrated workflow capabilities with Spark 2.0 integration to help simplify Hadoop and Spark application development. 

According to Syncsort, building an end-to-end data pipeline can be difficult and time-consuming, with various workloads executed on multiple compute frameworks, all of which need to be orchestrated and kept up to date. 

DMX-h was designed from the ground up to make big data integration simple, providing a single software environment for accessing and integrating all enterprise data sources – including mainframe access and integration capabilities  – and providing an easy-to-use graphical interface with the flexibility to quickly extend the software for organizations’ unique needs.

Syncsort's new integrated workflow enables organizations to manage various workloads such as batch ETL on very large repositories of historical data, referencing business rules during data ingest in a single workflow.

“With this integrated workflow, we can run multiple workflows, optimize for multiple compute frameworks in the same workflow, and we are also building the foundation for that,” said Tendü Yogurtçu, general manager of big data at Syncsort.

This new feature  simplifies and speeds development of the entire data pipeline, from accessing critical enterprise data, to transforming that data, and ultimately analyzing it for business insights, according to the company.

With the new version of DMX-h, developers can now also leverage Spark 2.0  to take advantage of the enhancements made in Spark 2.0.

They can visually design data transformations once and run the jobs in MapReduce, Spark 1.x or Spark 2.0, by simply changing the compute framework. No rewriting, reconfiguring or recompiling are required.

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