Continuing their ongoing coverage of SiliconANGLE’s own Big Data NYC Conference, John Furrier and Dave Vellante spoke with Jack  Norris, MapR CMO in theCUBE. The three discuss three myths associated with Hadoop and how MapR innovates.

Myth 1 – 

Norris challenges the idea that there is a vicious competition across Hadoop distributions. “In reality,” he says, “all distributions share same open source apache code.” Norris suggest this early stage must combine open source code with additional innovations to meet customer needs. There are diverse approaches in this area because there are aggregators taking open source, others that are taking open source and then adding management utility and other applications on top. Norris says MapR is distinguished as they take the open source with management innovations, and really focusing on the underlying architecture, the data platform and providing innovations at that layer.”

Myth 2 –

Secondly, Norris critiqued the NoSql myth noting, “there is no real consensus ,no common API, no real ability to move applications seamlessly around NoSql solutions.” He suggests this trend concerns compute and data together. Norris adds, “We shared some pretty interesting data [showing] the difference when you do architectural differences underneath. Not all NoSql is created equally, not all H-base is created equally.”

Myth 3 –

Perhaps the most pervasive myth is that Hadoop is not ready for primetime. According to Norris, “Disproving this myth only requires showing customer examples. We don’t have time in theCUBE here to go through all of them,” quips Vellante. Norris cites, “You look in traditional enterprise, a single retailer with over 2,000 nodes of Hadoop; financial services [have] over a 1,000 nodes with risk minimization and personalization as a key part of their financial operations.”

Vellante notes that customers consider it mission critical information. “If I’m going to use this as a key part of my recommendations, I want a consistent store,” says Norris. He suggests it can also be useful to do analysis directly on it to serve different business functions. MapR has current companies that have deployed an enterprise data hub.