Komprise natively integrates with NetApp. Use Cases:

Data Analytics Data Migration Data Archiving and Tiering, Data Replication Native Data Access
Any NAS to NetApp
NetApp AFF, FAS, E-Series
NetApp ONTAP
NetApp CloudVolumes ONTAP
NetApp StorageGRID
Azure NetApp Files, CloudVolumes Service

A DataFabric with Komprise data management and NetApp storage provides Pacific Biosciences a solid foundation for growth
Jay Smestad, Senior Director of Infrastructure Architecture, PacBio

Seamlessly Migrate, Tier, Archive, Replicate and Shrink Backup costs with NetApp and Komprise

NetApp and Komprise: Right Data, Right Place, Right Time
Get a single view of how NAS data across vendor platforms is growing, being used, and what data is hot or inactive and cold. Identify what data can move to NetApp – whether your use case is cloud tiering, migrating or tiering data to NetApp for performance or leveraging NetApp for capacity, Komprise can help.

Understand ROI of NetApp
Interactively tune your policies on what data you want to migrate, archive, tier and/or replicate to NetApp targets (NetApp FAS, E-Series, StorageGRID) and instantly visualize your savings and ROI.

Native NetApp Experience with Archiving and Tiering

Komprise is tightly integrated with NetApp to deliver a native experience for moved files – they look as if they were simply tiered from the NetApp, without any disruption to users or applications.

Access Data from NetApp StorageGRID or NAS with zero lock-in
Data moved by Komprise to NetApp StorageGRID or tiered or migrated to the the cloud are stored as objects, but fully accessible as files from the source NAS or from StorageGRID – with zero lock-in, no stubs, no agents.

Cost-Efficient Data Fabric with NetApp and Komprise
With sub-cloud pricing and a virtual-machine based solution that requires no dedicated infrastructure, you can seamlessly migrate, tier, archive and manage data and reduce cost and complexity.

Scale On-Demand
Scale as needed to handle petabytes and beyond by simply adding more virtual machines with no scaling limits or dedicated infrastructure

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