MapR Releases New Hadoop Distribution, Adds Quick-Start Solutions

Big data company MapR is eying new partner opportunities, better real-time data analytics and simpler self-service solutions for business intelligence with the release this week of the newest version of its Hadoop platform, as well as the introduction of new “quick-start” Hadoop applications for the enterprise.

Both developments support the trend toward “more self-service” for companies seeking to derive value from their data, MapR CMO Jack Norris said in an interview. The newest MapR release, version 4.1, includes, among other novel features, a POSIX client that makes it easier to connect to NFS data, as well as an API for C that enables companies to write Hadoop applications in that language.

MapR 4.1 also provides a way to synchronize real-time data analytics between data centers and locations. That functionality reflects the company’s belief that success in the big data world is “not just about providing more data, and more reports on data,” according to Norris. Instead, “what we’re seeing is a broader trend of companies that are doing things in real time.”

Meanwhile, the Hadoop quick-start solutions the company has introduced bundle particular MapR features to help organizations “get faster value in deploying applications,” Norris said. The quick-start solutions, which currently include applications for data-warehouse optimization, security log analytics and recommendation engines, can run in conjunction with either MapR’s enterprise or community Hadoop distributions.

Norris said the company expects to introduce additional quick-start solutions in the future. He added that MapR envisions these new products creating opportunities for MapR partners, who can integrate the quick-start solutions into their own platforms and services.

Alongside the new features and product announcements, MapR has been enjoying momentum in other areas recently. More than 5,000 people have registered for the Hadoop on-demand training courses the company introduced a few weeks ago, according to Norris, and GigaOM recently named MapR the best SQL-on-Hadoop solution.