Will March 2013 be the turning point where Big Data begins to noticeably eat away at the database establishment? In “Cracks in the Oracle Empire,” Wall Street Journal writer Steve Rosenbush reported Oracle Corporation executives blaming the sales force for “a disappointing quarter.” In fact, this is Oracle’s third miss in the last eight quarters, according to Michael Hickins.
Technology always changes, and Oracle, a pioneer in enterprise relational database technology, has been on top for years. Deservedly so, based on their many successful products. But innovation and excitement happen most often in smaller, hungrier, more nimble companies, and employees are drawn by that energy.
Just like automotive engineers who want to leave Detroit to join innovators like Tesla, programmers and sales people interested in Big Data want to join companies pushing into new areas. The core Open Source foundation of Big Data technologies like Hadoop, Cassandra, MongoDB, Storm, and R are fundamentally changing the economics of enterprise storage and processing.
When sales expenses increase, mainly due to turnover, that is a clear sign that Oracle is under pressure from new competitors, including Big Data. Looking beyond Oracle, at Think Big we see most traditional enterprise software, hardware, and legacy systems integration firms struggling to be relevant in a new world. New companies, powered by lean, efficient innovation that embraces diverse data sets to create value in a company’s core offerings, are gaining market share.
Oracle’s top, most experienced sales reps are leaving to sell Big Data, among other technologies, because they are finding that selling legacy approaches is getting a lot harder. The transition speed is accelerating.
As part of the new breed of Big Data companies, I’m often asked to brief Wall Street analysts about how this wave is remaking the world order. The trends have been clear, but now we’re starting to see just how fast this transition is rippling through the markets. March 2013 may be remembered as turning point from legacy relational databases, like Oracle, to the reduced cost and increased performance of Big Data.