MapR and Ericsson Team to Advance Hadoop+Spark Analytics

by Ostatic Staff - Feb. 23, 2016

MapR Technologies, which we've reported on extensively as it has focused on Hadoop and the Big Data space, has gained a powerful and experienced partner. It has formed a partnership with Ericsson, and the two companies are working together to advance adoption of the MapR Converged Data Platform. The platform integrates file, database, stream processing and analytics, and is gaining attention at enterprises. It's also interesting because it marries Hadoop and Spark, which are probably the hottest open technologies in the Big Data space.

“Ericsson has chosen to partner with MapR for its leadership in powering innovative data applications for some of the world’s largest organizations, said Peter Hartlev, head of PL data and storage, cloud, Ericsson.  "The MapR Platform is uniquely architected to unify open source with the utility-grade features our customers require, such as security, high-performance, reliability, and scale.”

The MapR Converged Data Platform brings together Hadoop and Spark with global event streaming; real-time, top-ranked NoSQL database capabilities; and enterprise storage. MapR claims that its platform provides "the fastest, most reliable, secure and open data infrastructure that dramatically lowers TCO and enables global real-time data applications for a broad set of business-critical and real-time production use cases."

By natively integrating data-in-motion and data-at-rest in a converged platform, MapR says it is looking to converge the message processing required for IOT, cross data center and public/private cloud  environments at what it is billing as "unprecedented scale."

 “We are pleased to announce our partnership with Ericsson,” said Patrik Svanström, vice president, EMEA, MapR Technologies. “Our combined technologies will bring tremendous value leveraging big data to support the broadest efforts on digital transformation in the communication service provider market and will enable our joint customers to quickly realize significant ROI and improve operational efficiencies in real time from their data.”

A blog post from MapR adds:

"When discussing big data we tend to focus on the end state -- the massive scale and variety of data required to cost effectively manage, analyze, and protect data. But big data is created one event at a time whether it is from sensors, log files, or customer interactions. MapR Streams makes it possible to better manage, analyze and distribute these events across locations, and subscribers. We’re talking up to billions of messages per second, millions of data sources, and over hundreds of locations.  Perhaps the most significant aspect of MapR Streams is that it is not a stand-alone system. It is part of the MapR Converged Data Platform. Data is reliability retained, available and protected by a full complement of advanced enterprise features. Data streams are exposed to a broad set of analytics, not just streaming analytics provided by Apache Spark or Storm, but also machine learning, database operations and more."