High-Performance Data Architectures for the Internet of Things

June 25, 2017

In recent years, the number of smart, connected devices making up the Internet of Things (IoT) has grown explosively. In 2009, when Cisco estimates the IoT was born, people were just beginning to play with micro-controllers to build smart devices. Since then, the number of devices has grown rapidly, and the IoT has expanded to include not just traditional computer-based devices and electronic appliances, but also wearables such as watches, clothing, and rings and vehicles, from the smart, self-driving cars currently in development to drones and other flying things. By 2020, Gartner expects the IoT to have over 20 billion connected things. With that many connected devices transmitting information, there will be an enormous amount of processing to be done. To cope with this rapid expansion in the Internet of Things, successful IoT platforms will need a data architecture that can address significant challenges in terms of speed, scalability, variable workloads, and other issues. What type of data architecture can handle these challenges?

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AVEVA

AVEVA is a global leader in engineering and industrial software driving digital transformation across the entire asset and operational life cycle of capital-intensive industries. The company’s engineering, planning and operations, asset performance, and monitoring and control solutions deliver proven results to over 16,000 customers across the globe. Its customers are supported by the largest industrial software ecosystem, including 4,200 partners and 5,700 certified developers. AVEVA is headquartered in Cambridge, UK, with over 4,400 employees at 80 locations in over 40 countries.

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