Syncsort Enhances DMX-h
February 20, 2017
enables organizations to accelerate business objectives by speeding
development, adapting to evolving data management requirements and
leveraging rapid innovation in Big Data technology. New Integrated
Workflow capabilities and Spark 2.0 integration dramatically simplify
Hadoop and Spark application development, enabling organizations to
extract maximum value from all their enterprise data assets.
“As Hadoop implementations continue to grow, with more diverse and
complex use cases, and a constantly evolving Big Data technology stack,
organizations require an increasingly efficient and flexible application
development environment,” said Tendü Yoğurtçu, General Manager of
Syncsort’s Big Data business. “By enhancing our single software
environment with our new integrated workflow capability, we give
customers an even simpler, more flexible way to create and manage their
data pipelines. We also extend our design-once, deploy-anywhere
architecture with support for Apache Spark 2.0, and make it easy for
customers to take advantage of the benefits of Spark 2.0 and integrated
workflow without spending time and resources redeveloping their jobs.”
Integrated Workflow Delivers Unparalleled Flexibility and Simplicity,
Accelerates Time to Insight
Building an end-to-end data pipeline can be time-consuming and
complicated, with various workloads executed on multiple compute
frameworks, all of which need to be orchestrated and kept up to date.
For example, an organization might need to access a data warehouse or
mainframe, run batch integration for large historical reference data in
Hadoop MapReduce, and run streaming analytics and machine learning
workflows with Apache Spark. Delays in development prevent business
users from getting the insights they need for decision-making.
With Integrated Workflow, organizations can now manage various workloads
such as batch ETL on very large repositories of historical data,
referencing business rules during data ingest in a single workflow.
The new feature greatly 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.
Built into Syncsort DMX-h’s design-once, deploy-anywhere architecture,
Integrated Workflow empowers developers to:
Dramatically reduce development time and resources by writing jobs in
one environment, such as a laptop, and running them anywhere, including
MapReduce, Spark 1.x or Spark 2.0, on-premise or in the cloud.
• Optimize with new technologies with an adoption pace that is best-fit
for their business with the ability to run each workload on the compute
framework that is best-fit for that workload.
• Enable organizations to leverage existing skills set and reduce by
using a graphical interface to easily create and combine sophisticated
workflows into one job, even if they are running on different compute
As a result of all the benefits of Integrated Workflow, developers have
unparalleled simplicity and flexibility to adapt to changing workloads,
allowing them to deliver faster time to insight, while minimizing
development and opportunity costs.
Spark 2.0 Support
Syncsort introduced Spark support in its last major release of DMX-h,
allowing customers to take the same jobs initially designed for
MapReduce and run them natively in Spark. With the new release,
developers can now leverage the same capability to seamlessly 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.