Full Cloud Data Management – Directly from the Mainframe

Announcing Model9 Cloud Data Manager for Mainframe v1.7

Tuesday, November 17, 2020 – Model9, a pioneer in cloud data management for Mainframe, is pleased to announce Model9 Cloud Data Manager for Mainframe v1.7. 

Version 1.7 is highlighted by the ability to perform all backup, archive, and restore operations directly from the mainframe to any cloud, on-prem, hybrid or public – eliminating the need to manage cloud data using external, non-mainframe systems.

As with previous releases, Model9’s software is designed to bridge the gap between mainframes and cloud, replace costly tapes and VTLs with hybrid cloud storage, and allow data analytics tools to directly process previously-inaccessible mainframe data.

Some of the major innovations in version 1.7 include:

Perform all operations from the mainframe.  With the addition of BACKUP and DELBACK commands, Version 1.7 provides a complete set of data operations that are performed directly from the mainframe – including backup, archive, restore, recall, list and delete – eliminating dependency on external systems, and enabling the integration of all common data management operations in scripts, automation tools and DevOps initiatives.

Faster, more effective migration of legacy backups.  Model9’s new BACKUP CLI command copies backup attributes from existing legacy storage management products to Model9 cloud storage.  Now, backups from legacy tools, such as CA-DISK and IBM DFSMShsm, can be quickly and simply migrated to the cloud – while preserving crucial metadata, and without having to perform redundant restore and re-backup operations – saving time and maintaining data quality levels.

Enhanced support for WORM storage.  Model9 support for Write-Once-Read-Many (WORM) cloud storage services, such as AWS ObjectLock and Hitachi HCP WORM Storage, is enriched through automatic detection of WORM-specific attributes. The improved awareness of WORM attributes helps prevent errors and saves valuable computing and operator resources, and enables compliance with data retention regulations for immutable storage media, such as SEC 17a-4.

Major scalability and performance improvements. 

  • Agents are enhanced to run multiple policies in parallel.
  • The Lifecycle Management process improved to support petabyte-scale data repositories. 
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