Model9 Cloud Data Platform

Model9 Cloud Data Platform modernizes mission-critical data operations and offers a seamless software-based solution to discover, move, transform and manage data in the private or public cloud.

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The Model9 Cloud Data Platform is an operating environment which includes a full set of core data management functions that are common to the cloud data management for mainframe suite of products.

Core Functionalities

Data Protection

Replacing legacy backup and space management software

Perform backup, archive, space management, and disaster recovery using cloud-based or on-premises object storage
Compatible with DFSMS
Create immutable data copies and air-gapped 3rd copies in the cloud with end-to-end compression and encryption

Data Storage

Replace your tape and VTL systems with cloud object storage

Write mainframe data directly to the cloud, with no need for interim DASD storage or having to rewrite JCL.
Transition to a cloud storage infrastructure
Eliminate the need for tape and VTL systems
Eliminate the need for expensive and complex tape management software

Mainframe Data Pipeline

Unlock your data for use by various cloud services, such as AI & BI tools and analytics services

Transform mainframe data (such as DB2 image copies) to standard or open formats – including JSON, CSV, and XML
Instantly access transformed mainframe data for integration with cloud-based applications
ELT (unlike ETL) – transformation is done in the cloud, letting you leverage cloud economics

Architecture

The Model9 Cloud Data Platform is made of two components – a zIIP-eligible agent running on z/OS and a management server running in a Docker container on Linux, Linux on Z, or zCX. The agent reads and writes mainframe data from DASD or tape directly to cloud storage over TCP/IP. A data set import policy provides automatic discovery of tape data sets and facilitates transferring large amounts of historical data from tape to the cloud.
Model9 uses the ELT approach (extract, load, transform), meaning the data undergoes transformation only after its transfer to the cloud. That process is faster and less expensive than traditional ETL (extract, transform, load), where any access to data requires transformation on the mainframe.

How it works

Automatically discover mainframe data sets and select the ones you want to backup, archive, or just write data to an object storage target, directly.
Move mainframe data according to flexible policies that best fits your business requirements to a lower storage tier in private / public cloud

Transform data into insights by seamlessly converting native mainframe data to common data formats
Manage, monitor and control mainframe data in a modern fashion, whether it is cold data kept in low-cost storage for backup, archive, or hot data that is accessed frequently by your mainframe applications