Why Syncsort introduced the mainframe to Hadoop

In an interview with IDGE, Josh Rogers and Lonne Jaffe of Syncsort explain how they plan to transform big iron and traditional data warehouse/analytics

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When you think of leaders in big data and analytics, you’d be forgiven for not listing Syncsort among them. But this nearly 50-year-old company, which began selling software for the decidedly unglamorous job of optimizing mainframe sorting, has refashioned itself into a critical conduit by which core corporate data flows into Hadoop and other key big data platforms. Syncsort labels itself "a freedom fighter" liberating data and dollars -- sometimes millions of dollars -- from the stranglehold of big iron and traditional data warehouse/analytics systems.

In this installment of the IDG CEO Interview Series, Chief Content Officer John Gallant spoke with Josh Rogers, who was named CEO this week, as well as outgoing CEO Lonne Jaffe, who remains as Senior Advisor to Syncsort’s board. Among other topics, the pair talked about why Syncsort was recently acquired by Clearlake Capital Group, and how Syncsort’s close partnership with Splunk is dramatically improving security and application performance management.

IDGE: Lonne, I understand you like good storytelling. What’s the story you tell IT leaders today about Syncsort?

Lonne Jaffe, Syncsort

Lonne Jaffe, Syncsort

Jaffe: Syncsort was founded in 1968. It was one of the very earliest software companies. I joined a little over two and a half years ago, and over the last couple of years the company has focused on this new mission around liberating data and liberating budgets from the stranglehold of legacy systems, while making the data and the budgets available for the fastest-growing data platforms in the world, things like Apache Hadoop and Splunk. Those platforms allow some of the interesting next-generation machine learning technology that we’re seeing manifest across all sorts of interesting industries like health care and self-driving cars and the Internet of things and the like. It has been a remarkable transformation in a lot of ways because people don’t usually think of a 48-year-old software company as the kind of entity that would be able to innovate around next-generation big data platforms organically.

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