Rocket Data Virtualization and IBM® mainframes: a winning combination for modern computing

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IBM z13s mainframeToday IBM introduced the z13sTM, a new version of the popular z13TM mainframe. If you haven’t heard about it yet, the z13s combines all of the power of the original z13 with an increased level of flexibility and more configuration options—all in a smaller physical footprint.

IBM also announced that all new IBM z13 and z13s mainframes are entitled to a full non-production license of Rocket Data Virtualization Version 2.1 (Rocket DV). If you’re not familiar with Rocket DV, it gives developers who have no mainframe experience the ability to move applications and analytics closer to their mainframe, and eliminate the need to move, replicate, or transform data. In other words, the mainframe data stays on the mainframe, and Rocket DV makes it easy to access that data in real time. So why does that matter?

Older approaches to data integration that rely on moving data, such as ETL technologies, are struggling to handle the extreme volume and diversity of data. There’s just too much data to justify moving it all into a data warehouse, and the desire of many organizations to support advanced analytics, mobile, and cloud initiatives means developers need a faster, more agile approach to data integration.

Data Virtualization is a big step forward in meeting this need, providing real-time access to data from nearly any device, regardless of format or location. Rocket DV makes it easy to (virtually) integrate data from multiple, disconnected sources into a single, logical, data source. You can then share that data with any application, providing the right data, in the right format, at the right time.

As an example, let’s think about someone who works in a Business Analyst role. For this person, mainframe data has to be fully accessible and available in a timely fashion. He or she needs data in minutes—not days. For that to be possible, the data needs to be (virtually) closer to the analytics. From a technical perspective, this means that enterprises must be able to effortlessly blend relational and non-relational data, mainframe and non-mainframe, and retrieve the combined information via a simple, single query or request. This means avoiding traditional data integration methods that move volumes of data into a central repository before analytics can be performed.

At the other end of the spectrum, CEOs are focused on increasing business growth and mitigating risk. For these users, the timeliness, accuracy, usability and accessibility of data are essential when it comes to making good decisions. To support this, the mainframe’s crucial role as the preeminent data server means a seamless integration with BI and analytics applications and core systems is vital.

Data integration solutions enable connections among people, processes, and systems with real-time information of value—regardless of source—so information to be shared across the enterprise, in real-time, giving users insight into evolving customer expectations, competitive threats and emerging market opportunities.

So when you get your new z13 mainframe, be sure to go to the IBM zDeveloper Community Hub website so you can get started with Rocket DV. I know you’ll like it. Want to know more about Data Virtualization? Ask me a question in the comment section below!

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Bryan Smith is Vice President of R&D and Chief Technology Officer at Rocket

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