Datos IO has announced a new version of its cloud-scale data management platform, RecoverX 2.0, to help organizations be more agile, enhance productivity, and drive operational efficiency as they deploy their next-generation customer-centric applications in the cloud and scale their traditional applications across hybrid-cloud and multi-cloud infrastructures.
Recognizing data as the only common denominator binding all clouds together, Datos IO aims to support customers in their journey toward cloud adoption, by introducing innovations, including an elastic compute engine that can be scaled up or down based on application needs; application-centric semantic deduplication that provides an order of magnitude higher storage efficiency than current approaches on both traditional and next-generation applications; rich data services, such as BI and search, built on top of a globally distributed metadata catalog.
Helping customers to leverage the promise of the cloud while eliminating cloud silos and facilitating complete data protection and mobility across a multi-cloud infrastructure, Datos IO says it allows enterprises to go beyond data protection to two significant use cases: easily exchanging data across siloed organizations and increasing application agility by enabling instant application deployments in the cloud.
Cloud data management is about reinventing the control plane with cloud principles in mind – elasticity, application-centricity, and scale, said Tarun Thakur, co-founder and CEO of Datos IO, noting that this is what enables customers to manage, protect, mobilize, and harness the value of their data across all cloud boundaries.
With the release of RecoverX 2.0, Datos IO extends its application-centric data management approach to migration of on-premise applications to and across clouds with new data mobility for relational databases. Organizations that are migrating traditional applications (starting with Microsoft SQL Server) to the cloud can now intelligently and efficiently move non-recovery workloads from on-premises to the cloud, across clouds, and from the cloud back to on-premises, with storage efficiency that is 10x that of traditional block-based or variable-length deduplication techniques.
The new release also offers cloud-native backup and recovery for traditional and next-generation applications, with data protection support for relational databases including Microsoft SQL Server hosted in private cloud or natively in public cloud environments, providing application-centric data protection regardless of deployment on physical server, virtual machine, or hyper-converged infrastructure (HCI).
RecoverX 2.0 also adds data protection support for Apache Hadoop distributions including Cloudera and Hortonworks providing petabyte scale backup and recovery for HDFS-based filesystems, fast recovery at file-level granularity, and unparalleled storage efficiency with file-based global semantic deduplication.
Datos IO has also added platform enhancements including elastic scaling, enterprise policy management, and operational metrics.
For more details, go to the Datos IO website.