Syncsort CEO on making the jump from the mainframe to Hadoop | #re:Invent2013
Hadoop presents an attractive value proposition for storing and processing large volumes of unstructured information, but it lacks certain enterprise features and requires specialized talent that is inaccessible to all but the wealthiest organizations. Companies that do not fall under this category face the added challenge of making their siloed data available to HDFS, a major barrier to entry that Syncsort is trying to remove.
A half-century-old software vendor that transitioned from selling data sorting tools to delivering Hadoop ETL on AWS, Syncsort is applying its expertise in legacy systems to help traditional enterprises stay competitive in the analytics era. Lonne Jaffe, the company’s newly appointed CEO, is doubling down on Big Data through an aggressive growth strategy that combines homegrown innovation and inorganic expansion.
We caught up with Jaffe at Amazon’s recently concluded AWS re:Invent 2013 event to discuss his gameplan and the recent acquisition of Circle, a UK startup that specializes in mainframe migration. The firm offers DL/2, a tool for moving IBM IMS and VSAM workloads to DB2 deployments running on z/OS.
Circle’s software frees up mission-critical data that was previously locked away in legacy IT environments, Jaffe explains. He says that the technology automates the time-consuming manual tasks associated with the migration process to accelerate time-to-insight and drive down costs.
“For the grownup companies who are using Hadoop: what good is your next generation Big Data cluster if it can’t access your actual data, and 70 to 80 percent of corporate data is still stored in the mainframe. So this allows them to get access to that mainframe data and also helps them to save a lot of money,” Jaffe details.
Once the data has been moved to DB2, it can be easily fed into Hadoop using Syncsort’s flagship ETL solution. The platform eliminates the need to upgrade legacy systems, according to Jaffe, enabling customers to use the batch processing as a preprocessor instead. Taking the latter route is not only cheaper, but it also lays down the groundwork for transitioning to Hadoop on an organization-wide level.
Check out the interview below for more exclusive details on Syncsort.
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