MapR Delivers Converged Data Platform

Look at the data infrastructure at many companies, and you'll still find silos of data that prevent culling the best possible insights with today's tools. MapR, which is focused on Hadoop, has its eyes on that problem. The company announced its MapR Converged Data Platform, which integrates file, database, stream processing and analytics.

By natively integrating data-in-motion and data-at-rest in a converged platform, MapR 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."

"Bringing together world-class Apache Hadoop and Apache Spark with a top-ranked NoSQL database and now continuous reliable streaming with global scale is a huge step forward in enabling enterprise developers to create the next-gen apps using big data," Anil Gadre, senior vice president, product management, MapR Technologies, said.

A blog post added:

"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."

"As coined by Gartner, Hybrid Transaction/Analytical Processing, is the new paradigm. The data to action lifecycle has to be real time so we produced a converged platform for Hadoop-style batch, interactive and streaming analytics where the same data also serves NoSQL database operations. Now with MapR-Streams we converge the message processing required for IOT, cross data center and public/private cloud environments at unprecedented scale."

You can learn much more about the new Converged Data Platform here.