Hadoop has been a phenomenon, both as a framework for big data workloads and its operational capabilities.
Major initiatives brought Hadoop from its batch-oriented roots to the interactive capabilities that are delivering improved performance in SQL engines and with distributed in-memory engines. Operational analytics are leading the way as “one of the first” steps towards operationalizing Hadoop as a platform. There are core data management principles that will guide Hadoop adoption, however there is also a change in mindset needed to rethink the role of Hadoop beyond a big data and analytic platform.
This paper examines the emergence of Hadoop as an operational data platform, and how complementary data strategies and increasing year-over-year adoption can accelerate consolidation and realize business value in agility and reduced development efforts.
MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. MapR brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified distribution for Hadoop.
Learn more about MapR at www.mapr.com.