NoSQL and Hadoop have given the database industry a shot of much needed sex appeal. But they present some adoption problems, especially for trying to use NoSQL and Hadoop to bring powerful analytic structure to massive volumes of discrete data, transforming simple data into actionable information.

Not only is Hadoop limited in its real-time data management abilities, but to leverage it, or any NoSQL solution, requires learning an array of proprietary coding techniques, raising project risk, increasing application code brittleness, delaying ROI, and causing vendor lock in.

This presentation outlines a unique approach to solving Big Data analytic problems within the context of an agile development methodology that respects the developer’s separation of concerns for richly linked algorithmic implementation from massive-scale MRP. It will demonstrate how integrating a unique object-oriented NoSQL database with Hadoop enables standard API's and skill sets to leverage the undeniable power of Hadoop's MapReduce.