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IoT Authors: Elizabeth White, Kevin Benedict, William Schmarzo, Pat Romanski, Rajeev Kozhikkattuthodi

Related Topics: Time Series Journal, Internet of Things Journal

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MapR Performance Benchmark Exceeds 100 Million Data Points Per Second Ingest

MapR Technologies, Inc., provider of the top-ranked distribution for Apache™ Hadoop®, today announced at the Tableau Conference, breakthrough performance results achieved using standard open source software, OpenTSDB, running on the MapR Distribution. Using only four-nodes of a 10-node cluster, the MapR Distribution with its in-Hadoop NoSQL database, MapR-DB, ingested over 100 million data points per second.

By accelerating OpenTSDB performance by 1,000 times on such a small cluster, MapR opens the doors to cost-effectively manage massive volumes of data and enable new applications such as Internet of Things (IoT) and other real-time data analysis applications, including industrial monitoring of manufacturing facilities, predictive maintenance of distributed hardware systems and datacenter monitoring.

“The accelerated performance for OpenTSDB validates the differentiated efficiency and scale that MapR brings to the table,” said Ted Dunning, chief application architect for MapR Technologies. “OpenTSDB is a widely used database intended to store and analyze time-series data. Originally designed for only data center monitoring, poor ingest performance had limited the expansion of its use. This benchmark demonstrates a viable option for new applications, such as IoT and other real-time data-analysis applications, using OpenTSDB running on MapR.”

According to estimates from Cisco, there will be approximately 50 billion devices connected by 2020. These IoT devices include sensors and other embedded data capturing devices that are communicating information continuously and pushing the boundaries of traditional data management platforms. Healthcare, manufacturing and utilities are examples of industries where decisions based on continuous data analysis can improve business operations. These devices will be phoning home and sending data. Time series databases will be critical to store and analyze these data sets.

MapR has published the details required to replicate these tests in the MapR App Gallery and on GitHub.

About MapR Technologies

MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. MapR brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified distribution for Hadoop. MapR is used by more than 500 customers across financial services, government, healthcare, manufacturing, media, retail and telecommunications as well as by leading Global 2000 and Web 2.0 companies. Amazon, Cisco, Google and HP are part of the broad MapR partner ecosystem. Investors include Google Capital, Lightspeed Venture Partners, Mayfield Fund, NEA, Qualcomm Ventures and Redpoint Ventures. MapR is based in San Jose, CA. Connect with MapR on Facebook, LinkedIn, and Twitter.

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