Big Data and Apache Hadoop are huge opportunities for channel partners. But the hype around Big Data is now overwhelming -- to a point where vendors seem to be using the term for every database, business intelligence, and cloud services tool they introduce. Time for a reality check from The VAR Guy.

First, the good news: A recent Hadoop Summit attracted 2,200 attendees and big-name sponsors like Amazon, Cisco Systems, IBM, Intel and Microsoft. And this week, VMware (NYSE: VMW) launched an open-source project, called Serengeti, that aims to let the Hadoop data-processing platform run on the virtualization leader’s vSphere hypervisor, GigaOm notes.

But each new Hadoop announcement also comes with a vendor agenda. VMware, for instance, wants to make sure Hadoop clusters don't eliminate the need for VMs.

The Hadoop and Big Data hype have been spinning out of control for about a year now. As Forrester Research's James Kobielus wrote in June 2011:
"At times, it almost feels like people discuss Big Data with the assumption that bigger is necessarily better and that throwing more data at your problems will automatically produce insights. I hope business and IT professionals heed my advice about searching for those special problems, often of a scientific nature, that can be solved best through petabyte-scale analytics. You don’t need a data center full of maxed-out storage arrays to derive powerful insights. Gut feel is free, and it often thrives on the scantiest information."

This Sounds Familiar

Hmmm... Here's The VAR Guy's spin on Big Data: It's a growing, potentially lucrative market for VARs that already understand analytics and business intelligence. But Big Data is more than Hadoop. If you focus on tried-and-true markets like Enterprise Data Warehouses (EDW) then you're likely in (or moving toward) the Big Data market -- even if you didn't know it.

During a Rackspace Partner Leadership Council meeting last week, Big Data came up as a hot topic several times. So the market is more than vendor hype. Just be careful of traditional tools that are suddenly re-branded and positioned for Big Data opportunities. Sometimes "New and Improved" isn't new, and isn't improved.