September 30, 2016 9:56 AM ET


Company Overview of MapR Technologies, Inc.

Company Overview

MapR Technologies, Inc. provides enterprise-grade distributed data platform to store and process big data. Its platform supports and brings speed to Hadoop, NoSQL, database, and streaming applications in one distribution for Hadoop. The company offers MapR M7, which provides distribution for Apache Hadoop with Hadoop database to run online and analytical processing on one platform; M5 edition, provides enterprise-grade Hadoop performance and management capabilities; and M3 edition for production use. It serves advertising, media, entertainment, data warehouse, financial services, government, healthcare, manufacturing, oil and gas, retail, technology and information services, and telecommunic...

2833 Junction Avenue

Suite 100

San Jose, CA 95134

United States

Founded in 2009



Key Executives for MapR Technologies, Inc.

Chief Executive Officer and Director
Co-Founder and Executive Chairman
Co-Founder, Chief Technology officer and Director
Chief Financial Officer
Age: 56
Chief Application Architect
Compensation as of Fiscal Year 2016.

MapR Technologies, Inc. Key Developments

MapR Technologies, Inc. Unveils Support for Event-Driven Microservices on Converged Data Platform

MapR Technologies, Inc. announced at Strata + Hadoop World comprehensive support for microservices that leverage continuous analytics, automated actions, and rapid response to better impact business as it happens. New capabilities in the MapR Platform range from microservices application monitoring and management to integrated support for agile microservices application development. Support for event-driven microservices relies on underlying new capabilities including: Comprehensive monitoring of cluster-wide operations and resource usage in a single pane of glass view. Microservices-specific volumes for application versioning, simplifying the development lifecycle and production deployment. Microservices for A-B and multivariate testing enabling rapid machine learning model development and optimization. Event-driven microservices on the MapR Converged Data Platform allow developers to have the freedom to combine a range of machine learning and analytic functions directly on the data. Microservices that seamlessly leverage file, database, and streaming services can be orchestrated on the Converged Data Platform with an underlying publish-and-subscribe framework that integrates data-in-motion and data-at-rest to support continuous and low latency processing. This highly effective approach integrates information from the latest events with deep insights from accumulated data. These microservices capabilities benefit from key features of the MapR Converged Data Platform including: Unified security with Access Control Expressions for data volumes, including streaming data. Support for agile and containerized application development on Docker, including applications with persistent data requirements. Converged analytic, processing, and messaging services in the same physical nodes for real-time requirements and greater simplicity. Support for hybrid cloud microservices architectures with global message service, global data namespace, bidirectional data flows with loop detection, and service scale out capabilities. Logical and functional isolation of services. Ideal for machine learning model training and evaluation. Continuous high availability and multi-master mission-critical disaster recovery capabilities. Microservices applications and other converged application development is simplified on the MapR Platform. Developers have the freedom to combine file, database, document, and streaming analytics functionality. With a single line of code, developers can easily persist complex data types with JSON in MapR-DB, so they can focus on developing innovative features. Customizable dashboards deliver full visibility of cluster hardware and software operations, utilization, and service logs. The Exchange, part of the MapR Converge Community, provides a public forum for sharing best practices around microservices, dashboards, and code snippets.

MapR Technologies, Inc. Announces Management Changes

MapR Technologies, Inc. announced the appointment of Matt Mills, previously president and COO, as chief executive officer and board member. Company founder and previous CEO John Schroeder will assume the role of executive chairman. He will remain involved fulltime with the company, continuing to partner with Mills while focusing on product vision and strategy, investor relations, and industry & customer relationships. Both executives assume their new roles effective immediately. This change is a natural evolution for the company, capitalizing on existing MapR leadership and positioning the company for further success. Mills and Schroeder bring strong complementary skill sets, mutual respect for each other, and have already proven to be a successful leadership team; the company has posted four consecutive quarters of record growth under their shared guidance. Mills is a seasoned industry veteran who brings a strong track record for leading high-growth organizations. He joined MapR after 20 years at Oracle, most recently leading the NA business while serving on the company’s executive committee. With his experience in scaling a business in a competitive market, Mills is well-suited to ensure that MapR capitalizes on its tremendous market opportunity.

CellOS Uses MapR Platform to Power Streaming Analytics for Telecommunications Applications

MapR Technologies, Inc. announced that CellOS Software Ltd. has deployed the MapR Converged Data Platform. CellOS will leverage the innovative features in the MapR Platform with Apache Drill and Apache Spark to offer its customers real-time data streaming applications to optimize the monetization of mobile broadband. CellOS will use the unique enterprise-grade features in the MapR Platform, such as its NoSQL database MapR-DB, with the schema-free analytics capabilities in Drill and the real-time streaming of Spark. CellOS will also deploy the Zoomdata stack to provide visual analysis of big datasets in seconds. The integration of these technologies enables CellOS to extract meaningful data in real time and quickly gain significant insights from data to create new revenue opportunities for customers.

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