Get Started with Hadoop in Just Minutes with the New MapR Sandbox

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3 min read

MapR has always been in the business of making Hadoop easier, and we believe we've made another big step forward with the MapR Sandbox for Hadoop. The MapR Sandbox gives developers and administrators the fastest and easiest way to get up to speed on Hadoop.

The MapR Sandbox is packaged as a freely downloadable virtual machine for VMware and VirtualBox. Since it contains a fully configured installation of the MapR Distribution for Hadoop, with advanced drag-and-drop functionality, users can get started in minutes. It includes the latest versions of Hadoop ecosystem projects such as Apache Hive, Apache Pig, Hue, and Apache Oozie. The included tutorials and browser-based interfaces round out the offering, giving users a complete, self-contained package for learning, developing, and testing.

The demand for Hadoop application developers continues to grow, as evidenced by a search on any job site. And we’re still in the early stages of enterprise Hadoop adoption. Developers around the world are seeking to jump on board to meet this demand. The MapR Sandbox gives them a valuable tool for augmenting their skill set to get into the huge job pool.

Developers aren’t the only ones who are actively seeking to boost the supply of Hadoop talent. Many of our customers, and Hadoop shops in general, see tremendous value in expanding Hadoop deployments throughout their enterprise. But in order to do so, they need to get more of their engineers ramped up. The MapR Sandbox is the perfect tool to supplement formal Hadoop training, so that engineers can continue to get hands-on exposure to Hadoop. They can navigate through the system, and quickly learn to build and test applications that can be deployed into the organization’s production system.

Check out our website product pages for more details.

To download and get started with the MapR Sandbox for Hadoop, click here.

To read our press release, click here.

This blog post was published February 12, 2014.

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