MapR has established itself as a frontrunner in the race to deliver the first truly enterprise-ready Big Data platform by diverging from the traditional open source approach to Hadoop, earning the scorn of rivals and others in the community. But by adding value-added features not supported directly in the batch processing platform, the firm has achieved a head start that is starting to pay massive dividends as adoption accelerates among large organizations.

“We’re seeing that open software is moving from the science fair phase where the people who were using it were the very early adopters…into an enterprise area, and the expectations are becoming very different: the expectations for continuity, maturity of implementation, [and] level of support. All of those notch up a lot when you sell to large organizations and when their business depends on it,” MapR chief application architect Ted Dunning explained on SiliconANGLE’s Studio B. The company addresses these requirements with proprietary components bolted onto Hadoop and packaged into commercial offerings, the newest of which enables users to run structured queries against data in HDFS.

Currently in early access, the HP Vertica Analytics Platform on MapR is an out-of-the-box solution for processing large volumes of semi-structured and structured information, complete with built-in BI and data visualization capabilities. SQL-on-Hadoop is not exactly new; similar functionality has been available with Cloudera’s Impala engine and the Hortonworks-led Stringer Initiative for a while now. However, MapR claims that using an established enterprise database gives its software an edge in performance while reducing hardware requirements, allowing customers to cut infrastructure and management costs.

The integration was announced at this week’s O’Reilly Strata Conference 2014 alongside support for YARN, the resource management and scheduling technology that replaces MapReduce in Apache Hadoop 2.0. On its own, the feature is not much of a novelty either, but the fact users can also run Hadoop 1.0 workloads in the same cluster is unique and provides a much-needed migration path for enterprises.

“As YARN expands Hadoop use cases in the enterprise, the need for enterprise-grade dependability, interoperability and performance increases exponentially,” said Tomer Shiran, the vice president of product management at MapR. “The combination of YARN and the MapR Data Platform delivers the only distribution for Hadoop in which both YARN and non-YARN distributed Big Data applications share the compute and storage resources of large-scale clusters.”

Finally, on Tuesday MapR released a pre-configured virtual machine loaded with a free version of its distro that can be set up in a matter of minutes. The package serves the same purpose as the Hortonworks Sandbox, providing a testbed for experimentation that lets practitioners get their feet wet before diving into production, and includes a collection of point-and-click tutorials for developers, analysts, and administrators.

Image source MapR