With New Partnership, Datameer Analytics Solution Trial Version is Included in the MapR Distribution

Datameer, Inc., a provider of end user analytics solutions built on Apache Hadoop, has announced its partnership with MapR Technologies Inc., and support for the MapR distribution for Apache Hadoop. The partnership will include joint technology and marketing efforts designed to accelerate the adoption and usage of Hadoop-based analytics. 

"The world of Hadoop is changing rapidly I think for the good," Joe Nicholson, vice president of marketing, Datameer, tells 5 Minute Briefing, observing that customers now have more choices and more enterprise-class functionality available to them, making it more comfortable for large, established companies to select Hadoop.

Founded by Hadoop veterans in 2009, the company's product, Datameer Analytics Solution (DAS), scales to 4,000 servers and petabytes of data and is available for all major Hadoop distributions including Apache, Cloudera, Yahoo!, IBM, and Amazon, and now MapR.

"We are basically a BI platform, packaged BI, on top of Hadoop. We are agnostic as to the distribution. We don't want to point at any one direction, but let the customer decide what distribution they want," says Nicholson.

Enabling business users to access, integrate and analyze massive amounts of structured and unstructured data, DAS leverages the linear scalability and the cost-effectiveness of Hadoop while masking its technical complexity. "Our mission in life is to be able to provide packaged BI functionality directly to the business user," explains Nicholson

As part of the partnership, a full-featured, trial version of the DAS will be included in the MapR distribution and will be available for download. Datameer has certified its Datameer Analytics Solution for the MapR distribution and says it is including its trial version together with sample pre-processed MapR and related datasets, analytic workbooks and dashboards with the MapR download to illustrate to users how powerful and easy it is to perform big data analytics.