Imanis Data bets its data management farm on machine learning Backupbot

By Chris Mellor 06 Sep 2018 at 14:57

Imanis Data, the distributed database backup vendor, says it is the first company to introduce an autonomous backup product powered by machine learning. Is this the first Backupbot?

The system makes backup decisions

Users specify a desired RPO (Recovery Point Objective) and Imanis SmartPolicies sets up the backup schedules. The technology is delivered as an upgrade to the Imanis Data Management Platform (IDMP).

Version 4.0 see the introduction of ‘SmartPolicies’, which uses metrics including desired RPO, criticality and volume of data to be protected, primary cluster workloads, and daily or seasonal resource utilisation, to determine the most efficient way to achieve the desired RPO.

If it can’t be met, because, for example, production systems are too busy, or computing resources are insufficient, SmartPolicies provides recommendations to make the RPO executable.

The IDMP upgrade includes any-point-in-time recovery for multiple NoSQL databases, better ransomware prevention and general data management improvements, such as job tag listing and a browsable catalog for simpler recovery.

Imanis has rounded up this canned quote from Christophe Bertrand, senior analyst for data protection at ESG Research: “The data protection market in this space is underserved by traditional vendors and Imanis Data with their unique machine learning approach is setting the bar for Hadoop and NoSQL enterprise data management.”

Supported Hadoop, and NoSQL platforms include Apache Cassandra, Apache HBASE, Cloudera, Couchbase, DataStax, Hadoop, HDInsight, HortonWorks, Microsoft ADLS, MongoDB, and Vertica platforms.  Additionally, the latest release includes usability enhancements to Imanis Data FastFind including job tag listing and a browsable catalog for simple recovery.

Imanis says the anti-ransomware addition, ThreatSense, has so-called Intelligence Augmentation which allows users to report false positives only identifiable through human observation; implying the machine learning has misled them, because; this data is fed back into the machine learning model, eliminating specific anomalies and making its ransomware detection more effective.


Backup software that sets up its own schedules based on input RPO values is not a new idea, but using machine learning to do this is a novel technique. The checking if available resources is a darn good idea too and, when you think about it,  necessary.

Otherwise “Backup run failed” messages would start popping up all over the place. Not good. We anticipate more backup vendors to follow in the wake of Imanis and start sporting “machine learning-driven policy” messages.

This Imanis v4.0 software is the first major release since incoming CEO John Mracek took over the reins in February. Imanis Data, which renamed itself from Talena in 2017, has been in Datos IO’s shadow. When that company was bought by Rubrik the  NoSQL backup technology area became validated and Imanis is now betting its future on Backupbot distributed database/NoSQL protection becoming successful. 

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