Big Data. Big Decisions
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George Crump

One Backup App For Enterprise: Not Here Yet

Patchwork backup systems for virtual and non-virtual parts of the enterprise, with no centralized view, make protecting data more time consuming and more expensive than it should be.

Data centers undergo constant change--new applications and operating environments are added all the time. With each of these changes, new data protection challenges arise. New software applications are created to solve the unique protection challenges these environments create. But it's hard to find a single data protection solution that answers all the demands of an enterprise.

An excellent case in point is the flood of products focused on protecting the virtualized environment, VMware specifically. These products are fine tuned to make data protection of the virtualized environment easier and to take full advantage of the abilities that the virtualized environment can provide such as changed block tracking for smaller backups and instant recovery of virtual machines from the backup target.

A potential weakness of these virtualization-specific backups is that they do not support protection of the non-virtualized part of the data center, which according to some reports is 50% or more of servers. Although the data center is moving toward 100% virtualization, it is going to take a while to get there. The remaining systems typically stand alone for a reason and virtualizing them might be a problem. The backup administrator is left running a separate backup application for as much as 50% or more of the data center.

As we discussed in two recent reports, From Backup Utility To Complete Solution and Unifying Virtualized Backup, Replication and Recovery, some VM-specific backup applications are adding non-virtualized server backups to their capabilities. But there are other needs that so far only enterprise backup applications are providing such as tape support and robust online backups.

To make matters worse, other applications--databases in particular--often have their own eco-system of data protection solutions. As is the case with the virtualized environment, these utilities provide advanced data protection capabilities for their specific environment that enterprise applications don't.

This leads to a fragmented data-protection strategy where VMware administrators pick the application they want to protect their environment, application owners pick the application they want to protect theirs, and the enterprise backup application is left protecting the leftovers--and often protecting the virtualized and application environments a second time. The result is a data protection process that is more complex and more costly than it should be.

So how do you get the best of all worlds if you have mission-critical applications that are not going to be virtualized soon? As we will discuss in our upcoming webinar, The Four Things That Are Breaking Enterprise Backup, the enterprise applications need to evolve into data protection engines that provide basic protection; advanced back-target support for tape and disk backup appliances; cataloging; scheduling; and policy management.

Many enterprise backup applications provide these capabilities today, but these capabilities are locked within the application. What they need to do is open them up by providing a framework or API set. Then application-specific data protection products could plug into these engines. This would give the backup administrator a centralized view of the data protection process but the application owners specific capabilities that make their jobs easier.



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By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



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