These limitations have created huge friction for companies in the cloud computing era. Backing up mainframe data in modern cloud storage has traditionally required either transforming it into open formats in the mainframe first, or altering mainframe applications to be compatible with cloud. Neither of these options is ideal; they drive costs up, do not overcome the performance cap inherent to serialized protocols, and silo mainframe data away from cloud analytics applications.
Cloud’s relationship to mainframe data backup was ripe for disruption. Today, Model9—a global company with a presence in enterprise companies everywhere from North America to EMEA—is helping enterprise organizations leverage cloud technology faster, more easily, and at lower cost.
Cloud data management for mainframe
Model9 believes mainframe backup requires modernization — eliminating legacy mainframe data management tools and replacing them with modern backup, archive, space management, and disaster recovery tools in the private, public, or hybrid cloud.
Its Cloud Data Manager for Mainframe is patented technology that allows companies to transfer any disk or tape data (current or historical) directly to and from the cloud with no need for interim disk storage or mainframe application changes.
“The transition we make possible has immediate positive impacts. It reduces and eliminates CapEx, controlling OpEx, and opening top-line opportunities to monetize the latent value of data,” states Gil Peleg, Model9’s Founder and CEO.
Cloud backup, archive, space management and disaster recovery can be implemented directly from the mainframe to any cloud or on-premises storage system.
This bi-directional flow offers companies the flexibility to pursue an affordable, long-term archiving strategy for hot and cold storage, and also to restore mainframe data directly from the cloud in the case of disaster.
“Model9 Cloud Data Manager for Mainframe creates a bi-directional flow of data between your mainframe and cloud so you can eliminate legacy data management solutions and backup, archive, and recover your data directly in the cloud,” said Peleg.
Reduced costs and complexity for the enterprise cloud-mainframe connection
Model9’s Cloud Data Manager for Mainframe already delivers higher performance at lower cost.
A US-based bank had been dependent on the Oracle StorageTek Virtual Storage Manager (VSM) System for writing to on-prem tape storage, a resource-intensive and time-consuming process. To reduce the time required to complete their backup jobs, Model9 replaced the bank’s VTL and backup software and wrote data directly to object storage in the Azure public cloud. Throughput soared from 27MB/s to 547.96MB/s, reducing the required time between backups from 24 hours to 1 hour and 11 minutes.
In the future, Model9 intends to write mainframe data directly to the cloud, bypassing not only legacy backup and archive solutions but also DASD storage itself via its cloud data sets feature. In addition, existing Data transformation features continue to unlock mission-critical mainframe data that until today was locked inside the on-prem data silos created by legacy storage tools.
De-emphasizing the mainframe’s physical hardware, while augmenting its huge potential to be a game-changer for cloud data analytics applications, is the vision of the future Model9 is building today.
“Whether pursuing a cloud-first strategy or simply aiming to populate your BI/ML data lake with your most valuable data resource—the data in your mainframe—Model9 addresses this impulse to do more with data and extract its full value as quickly and efficiently as possible,” Peleg said