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Your Data Lake Doesn’t Have to Miss Out on Mainframe Data!

Danielle Zubery

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Nov 4, 2020

In modern analytics, significant value can be gained from insights that are based on multiple data sources. That’s the power of the data lake concept. But for most larger organizations, unaware that there are easy data movement options, data lakes still exist far from the organization’s most important and often largest data collection—the data in mainframe storage. 

Whether this data is already at home in a mainframe data warehouse or scattered in multiple databases and information stores, its absence from the data lakes is a tremendous problem.

In fact, in an Information Age article, Data Storage & Data Lakes, editor Nick Ismail noted, “If an organization excludes difficult to access legacy data stores, such as mainframes, as they build the data lake, there is a big missed opportunity.”

Recognizing this growing business challenge, Model9, a company founded by mainframe experts and cloud evangelists, created unique, patented technology that can move mainframe data and transform it to and from standard industry formats and between the cloud and mainframe. Specifically, Model9 eliminates the traditional ETL process, which is expensive in terms of time, money and CPU cycles, and delivers richer outcomes with fewer resources. 

In other words, Model9 helps get mainframe data into the game. 

Unlike traditional brute force methods of moving data to other platforms, requiring heavy use of mainframe processing power, Model9 does most of the work outside of the mainframe, a process of extract, load, and transform (ELT) rather than extract, transform, and load (ETL). It is fast and economical.

Model9 | Diagram | ETL vs. ELT

Is it really that easy? Yes. The Model9 architecture includes a zIIP-eligible agent running on z/OS and a management server running in a Docker container on Linux, z/Linux, or zCX. The agent does the job of reading and writing mainframe data from DASD or tape directly to cloud storage over TCP/IP using DFDSS as the underlying data mover.  Other standard z/OS data management services are also used by the agent, such as system catalog integration, SMS policy compliance, and RACF authorization controls. Compression and encryption are performed either using zEDC and CryptoExpress cards if available, or using zIIP engines. 

Although the world of DB2 tools on mainframe has made a lot of progress  in integration with other SQL databases by using CDC technology, this remains an expensive approach and one that does not scale optimally. In contrast, the Model9  Image Copy transformation offering is an industry-first lift & shift solution for DB2 on mainframes.

Additionally, Model9 offers migration capabilities  for unstructured mainframe data types such as VSAM, PS, and PO as well as support for COBOL copy books, delivering end-to-end process automation.

Presto, organizations can now easily share mainframe data with analytic tools and incorporate it into data lakes, potentially yielding powerful insights.  Model9 offers data lakes a chance to reach their fullest potential and makes mainframe pros into business partners!

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About the author

Danielle Zubery | Marketing Manager
Danielle has been in the B2B marketing space for the past 5 years, where she excels in creating and scaling demand for products in new spaces.

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