Software Development

Gartner 2016 Magic Quadrant for Data Warehouse and Database Management Solutions for Analytics

We are excited to share with you that Gartner has named MapR a Visionary in the Gartner 2016 Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics. Gartner evaluated 21 software vendors on 15 criteria for the quadrant. The MapR Converged Data Platform enables customers to leverage a real-time, reliable analytics platform for global data-driven applications.



Figure 1. Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics
Figure 1. Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics

Source: Gartner (February 2016) This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request here.

According to Gartner, “Organizations now require data management solutions for analytics that are capable of managing and processing internal and external data of diverse types in diverse formats, in combination with data from traditional internal sources. Data may even include interaction and observational data — from Internet of Things sensors, for example. This requirement is placing new demands on software in this market as customers are looking for features and functions that represent a significant augmentation of existing enterprise data warehouse strategies.”

A Leader in Enabling Global, Real-Time, Data-Driven Applications

At MapR, we believe that we’re a leader among companies that provide data warehouse and data management solutions for analytics due to our MapR Converged Data Platform, which integrates Hadoop and Spark, real-time database capabilities, and global event streaming with web-scale storage for developing and running innovative data applications in a single cluster. The MapR Platform is powered by the industry’s fastest, most reliable, secure, and open data infrastructure that dramatically lowers TCO and enables global, real-time, data-driven applications.

A Leader in Addressing Streaming, Operational, and Analytical Use Cases

The MapR Platform addresses these use cases by delivering a comprehensive set of technologies, including SQL capabilities via Apache Drill and other SQL-on-Hadoop engines. The core components of MapR include:

  • Apache Hadoop – an open source framework for processing large volumes of data across many commodity servers, running on the utility-grade MapR Platform Services for a more powerful and protected production big data deployment
  • Apache Spark – an increasingly popular open source in-memory data processing engine that enables faster application development and higher performance, with complete support from MapR for the entire stack
  • MapR Streams – a global publish-subscribe event streaming system for big data
  • MapR-DB – a high performance, in-Hadoop NoSQL database management system
  • MapR-FS – the underlying POSIX file system that provides distributed, reliable, high performance, scalable, and full read/write web-scale data storage

That is the crux of our work here at MapR. It’s why we developed the MapR Converged Data Platform, which converges data streaming, operational, and analytic applications in a single cluster and redefines what’s possible in terms of enabling developers to build new and exciting applications. Our products have become the technology backbone for many of the largest companies of the world, including household names like American Express, Cisco, Comcast, Ericsson, IRI, Novartis, Qualcomm, Rubicon, Samsung, and UnitedHealthcare Group, among many others.

By bringing together a converged system that provides interfaces for files, tables, and streams in one unified platform where it’s secured, managed, highly available, completely distributed, with best-of-breed technologies, you get a powerful innovated platform for your global, data-driven applications. We look forward to providing continuous innovation to help you address your modern data challenges.

Helpful links for further information:

Gartner: Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics, Roxane Edjlali and Mark A. Beyer, 25 February 2016.

Note: Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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