One immediate benefit, he notes, is the ability to rapidly prototype in the cloud and then seamlessly bring the solution on-premise using the common platform offered by Windows Azure HDInsight Service and Microsoft HDInsight Server for Windows.

"Early experimentation and testing in the cloud eliminates early capital expenditures that can be a barrier to adoption," Adrian says. "For example, Amazon's AWS has been used for millions of Elastic MapReduce jobs, but those experiments stayed in the cloud. The connection of cloud to on-premise systems offers the promise of more rapid time to value-and Microsoft has established a lead in connecting to its widely used stack."

Microsoft's Leland notes the capabilities provided by the two flavors of HDInsight also allow customers to run most of their big data analytics on-premise but cloudburst to Azure when they need the additional compute.

"Ultimately it's an ideal scenario," he says. "You can manage your infrastructure cost, but really have unlimited scale when you need it. You can spin up a cluster in less than 10 minutes [in Azure]. Having that kind of additional capacity, that quickly, on demand, that simply, is certainly going to change the game."