Last week, Symantec and Microsoft announced a joint effort to deliver Disaster Recovery as a Service (DRaaS). This hybrid approach will involve using Symantec Storage Foundation HA for Windows on the customer premises to provide data replication and failover management to Microsoft's Azure cloud services. This is a pretty big deal.

While our largest customers have the luxury of multiple data centers spread across a large area, most companies don't. With multiple data centers, a company can provision additional capacity in each one to host another data center's critical applications in the event of a site failure. But in the absence of additional real estate, a company's options for disaster recovery are more limited. And this is where DRaaS comes into play.

This service will allow smaller organizations to acquire virtual real estate in the form of Microsoft's...

What does Big Data mean to enterprises?

How does this change their storage architecture?

Does the need for taking advantage of Big Data analytics mean a cluster of 1000s of compute nodes?

The answers create lot more confusion than clarity and it depends on who you ask. In an attempt to add clarity to the conversation I sat down with  V.R.Satish, CTO of Storage and Availability Management Group at Symantec to get his thoughts on how enterprises should approach the Big Data storage problem.

Here are some excerpts from my conversation.

Rags: Satish, we keep hearing about the data deluge, growth and variety. How do you think enterprises must approach Big Data?

Satish: As always with any business decision, start with the problem we are trying to solve, focus on the value realization and how it will help you better serve your internal and external customers. How you approach the problem and...

In my previous article I wrote about the five factors that limit Hadoop's role in the enterprise datacenter. To recap, the limitations are,

1. Increased storage sprawl
2. Three times as much storage
3. Costly data moves
4. Single point of failure
5. No support for backup

The first three issues stem directly from the architecture choice recommended for Hadoop clusters - use of many different compute nodes, each with its own embedded Direct Attached Storage (DAS).   Enterprises choosing Hadoop are forced to make the trade-off of accepting these limitations in favor of getting the power of Hadoop analytics.  Is DAS the only choice despite its limitations?

In a very well researched article, John Webster of Evaluator group poses and answers the question on...

The biggest driver for adoption of Hadoop is its promise of unlocking value from an enterprise’s vast data store. Use cases that show incremental revenue from data analysis are very well publicized.  Every organization strives to achieve that and wants to leverage the power of data analytics to drive its revenues. Promises aside, Hadoop storage has severe issues that calls  into question its place in the enterprise datacenter.

1. Increased storage and server sprawl – Hadoop cluster is built  with numerous commodity hosts, each with its own direct attached storage. Just when datacenter architects have spent considerable time and resources consolidating their datacenters and reducing footprint through server consolidation, virtualization and private cloud,  Hadoop requires them to build out a massively parallel system with hundreds or even thousands of compute nodes. Managing these numerous nodes and keeping them up to date...