Protection, Orchestration, Automation: The Pillars of Enterprise Data Management

The Need for a Fresh Approach to Enterprise Data Management

Driven by the need to remain competitive and differentiate themselves, organizations are undergoing digital transformations and becoming increasingly data driven, constantly looking for ways to harness the value of their data to enable smarter decision making and to create better user experiences. The unprecedented volume of data being created and the need to store, access, and harness the value of that data has created fundamental shifts in IT:

  • The shift from on-premises only infrastructure to hybrid-cloud infrastructure is the new normal – public cloud platforms/services (e.g. AWS, Azure) have become a critical pillar of virtually every organization’s IT infrastructure.
  • Organizations are increasingly migrating from SQL databases (Oracle, SQL*Server) to Hadoop and NoSQL distributed data platforms (e.g. MongoDB, Cassandra, DataStax, Hadoop, Hive, Hbase) for their modern, microservices based applications like IoT, eCommerce, Customer 365, and SaaS.
  • Business Criticality of Modern Applications – modern, distributed microservices based applications have become business critical in the new economy and the data associated with these applications needs to be managed.

These changes in aggregate have created a major challenge for CIO’s who have to-date relied on legacy data management vendors like Commvault, Dell EMC, IBM, and Veritas, as well as more recent incumbents like Veeam, Rubrik, and Cohesity, for their data management needs. While all of these vendors have considerable market share in the traditional on-premises, RDBMS-centric data management market, their legacy architectures are not designed to be useful in the new world of hybrid cloud and distributed databases. CIO’s need to embrace new technologies in order to address their data management needs.

Enterprise Data Management…Powered by Machine Learning

In response to these challenges, Imanis Data developed the world’s first enterprise data management platform powered by machine learning. The Imanis Data Management Platform enables customers to efficiently manage their Big Data and NoSQL data on-premises or in the cloud by delivering three key capabilities:

COMPREHENSIVE PROTECTION – is the first order of business for data management and includes backup, recovery, and disaster recovery ensuring organizations can recover from data loss and downtime caused by natural or man-made events. Imanis Data protects all of your Hadoop and NoSQL data on-premises or in the cloud with a combination of powerful capabilities including petabyte scale incremental forever backup, granular recovery, unparalleled restore performance, multi-stage data reduction, and agentless connection to all data sources.

POWERFUL ORCHESTRATION – is the key to reducing cost, ensuring compliance and harnessing the power of hybrid cloud infrastructure by enabling organizations to copy, move, or migrate data to the appropriate location based upon use-case (e.g. test/dev, archiving, database migration, and cloud instantiation). Imanis Data orchestration services include a global metadata catalog for visibility to data wherever it resides, a flexible policy engine for move and copy operations, data masking, data sampling, and data filtering.

PREDICTIVE AUTOMATION – leverages machine learning to intelligently automate the protection and orchestration of all your data. Using patent pending machine learning services Imanis Data helps organizations ensure compliance, optimize RPO and RTO, reduce storage costs, enable data insight, and protect against cyber-attacks.

Customer Impact

By delivering these Protection, Orchestration, and Automation, only Imanis Data is able to provide technical, operational, and financial value to our customers, including:

  • Reduced Risk
    • Application consistent, point-in-time backup means your data is always recoverable.
    • Lightning fast recovery restores your data to Busimeet your RTO needs
    • Masking PII data prior to copying to a non-production database reduces compliance risk
    • Machine learning powered ThreatSense provides a line of defense against ransomware attacks
  • Operational Efficiency
    • Replaces manual scripting with policy automation and single-click orchestrated recovery
    • Automated refresh of test/dev data sets eliminates manual overhead
  • Simplicity
    • Single pane of glass for all your Big Data and NoSQL data management requirements.
    • One solution for all your key use-cases including backup and recovery, disaster recovery, test/dev refresh, and archiving
  • Reduced Costs
    • Multi-stage data reduction and global deduplication can increase backup storage efficiency up to 90%
    • Sampling down data reduces size of test/dev environments
    • Linear scalability enables you to grow as you go with no wasted capacity

To learn more about how we do all of this, check out our product page here.

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