Hortonworks launched a new trial version of Hadoop that enables users to run the analytics engine on a desktop with minimal setup. It’s infinitely more accessible than downloading and deploying the Apache versions of these projects.
Marketing director Cheryl Custer explained the purpose behind the new solution, dubbed Hortonworks Sandbox, in a blog post she published this morning:
“The Hortonworks Sandbox is designed to help close the gap between people wanting to learn and evaluate Hadoop, and the complexities of spinning up an evaluation cluster of Hadoop,” the executive wrote. “The Hortonworks Sandbox provides a powerful combination of hands-on, step-by-step tutorials paired with an easy to use Web interface designed to lower the learning curve for people who just want to explore and evaluate Hadoop, as quickly as possible.”
Sandbox is a standalone solution that runs inside a self contained, pre-configured virtual machine scaled down to PC proportions. The software gives both academics and potential Hortonworks clients the opportunity to get a feel of what Hadoop has to offer before ever committing to a financial investment.
The single-node distribution is based on the latest release of the Hortonworks Data Platform, which was only rolled out debut last week. The main improvement that v1.2 offers over previous versions is native integration with the Apache Ambari configuration tool, but it it’s only one of several tweaks. Hortonworks also said that it has re-architected HDP to be more secure, and claims to have enhanced HBase so that it now reads and writes data faster.
Automation is one of the top priorities in big data today. Hadoop and the associated Apache projects are all free, but they are still out of reach for the majority of organizations that can’t afford a resident team of data scientists. That’s why Hortonworks and its peers are working on making big data simpler and more accessible for more audiences.
Latest posts by Maria Deutscher (see all)
- Pentaho doubles down on Hadoop and Spark - September 26, 2016
- Podium Data raises $9.5M to make Hadoop-based data lakes a reality - September 26, 2016
- What you missed in Big Data: AI continues to gain momentum - September 26, 2016