Syncsort's Latest Innovations for Apache Kafka & Apache Spark Support Leading Big Data Streaming Use Cases

WOODCLIFF LAKE, N.J., Sept. 29, 2015 /PRNewswire/ -- Syncsort, a global leader in Big Data software, today announced new integration of its industry leading data integration software with Apache Kafka and Apache Spark that enables users to leverage two of the most active Big Data open source projects for handling real-time, large-scale data processing, analytics and feeds.

"Many organizations are interested in using a single software environment for streaming and batch processing, while taking advantage of the power of the Apache Spark compute platform for analytics and the speed and resiliency of Apache Kafka for low-latency, fault-tolerant services," said Tendü Yoğurtçu, General Manager of Syncsort's Big Data business. "We are seeing increased demand for real-time analytics in industries such as healthcare, financial services, retail and telecommunications. With these important announcements, we are advancing our Big Data strategy by delivering a powerful next generation streaming ETL and Internet of Things data integration platform."

New Integration for Apache Kafka

Syncsort DMX-h, Syncsort's industry leading data integration software, now integrates with the Apache Kafka distributed messaging system, so users can leverage DMX-h's easy-to-use GUI to subscribe, transform, enrich and distribute enterprise-wide data for real-time Kafka messaging.

"Apache Kafka is widely adopted for a variety of use cases involving real-time data streams and is changing how data is used in companies," said Jay Kreps, co-founder and CEO for Confluent. "We are excited that Syncsort has integrated its high performance data integration technology with Kafka to help customers collect, enrich and supply data from company-wide sources via an easy-to-use graphical interface."

New Integration for Apache Spark 

Syncsort recently delivered an open source contribution of an IBM z Systems mainframe connector that makes mainframe data available to the Apache Spark open-source analytics platform. Now, Syncsort is integrating the "Intelligent Execution" capabilities of its DMX data integration product suite with Apache Spark. Intelligent Execution allows users to visually design data transformations once and then run them anywhere – across Hadoop, MapReduce, Spark, Linux, Windows, or Unix, on premise or in the cloud.

"Organizations look to Spark to enable a variety of use cases, including streaming data analytics across diverse data sources," said Matei Zaharia, creator of Apache Spark and co-founder & CTO of Databricks. "Syncsort has recognized the importance of Spark in the Big Data Ecosystem for real-time streaming applications and is laser-focused on making it easy to bring diverse data sets into Spark."

Syncsort's continued commitment to Big Data innovation was recently recognized again when the company was named the Big Data Quarterly's Big Data 50.

For more information on DMX-h, click here. To learn more about our Apache Spark and Apache Kafka integration, visit us at Strata + Hadoop World this week. To register for a technical preview of our Apache Kafka integration, click here. To download the Spark Mainframe Connector on Spark Packages, click here.

About Syncsort

Syncsort provides enterprise software that allows organizations to collect, integrate, sort and distribute more data in less time, with fewer resources and lower costs. Syncsort software provides specialized solutions spanning "Big Iron to Big Data," including next gen analytical platforms such as Hadoop, cloud, and Splunk. For more than 40 years customers have turned to Syncsort's software and expertise to dramatically improve performance of their data processing environments, while reducing hardware and labor costs.  Experience Syncsort at http://www.syncsort.com.

Media Contacts:

Sarah Borup     
SHIFT Communications
Tel: 617-779-1803
[email protected]

Michael Kornspan
Syncsort Incorporated
Director, Corporate Communications
Tel: 201-930-8216
[email protected]

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SOURCE Syncsort

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