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Objectivity Introduces Information Fusion Platform to Enrich Big Data with Fast Data

With ThingSpan, enterprises can derive better value from fast data for applications associated with the industrial Internet of Things.

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

Objectivity, Inc. has introduced ThingSpan, a purpose-built information fusion platform that simplifies and accelerates any organization’s ability to deploy industrial Internet of Things (IoT) applications to enhance value derived from big data and fast data. ThingSpan is a massively scalable distributed solution for information fusion designed specifically for the complex issue of extracting actionable insights from fast data and architected to integrate with major open source big data technologies.

With the growth in use of massive sensor networks, organizations have been facing challenges getting industrial IoT applications into production. As a result, most enterprisesstruggle to effectively use data from sensors and other streaming sources in their business operations. A recent report from McKinsey & Company about IoT stated that in many industries, less than 1 percent of sensor-based data is actually analyzed. The same report shows that better utilization of sensor-based data could lead to positive impact of $3.9 trillion to $11.1 trillion per year by 2025 through improved productivities.

“Since our founding, Objectivity has been pursuing data management challenges for applications involving the most complex data sources. As part of this effort, Objectivity has been working with leading systems integrators and organizations building advanced data and information fusion solutions for more than a decade,” says Jay Jarrell, CEO of Objectivity. “ThingSpan accelerates time-to-production of fusion applications by providing key capabilities in an information fusion platform.”

Fast data differs from other data in that it is generated in high volume, its value is time-sensitive, and it is made up predominantly of time-series data. However, the sheer volume of fast data presents a complex problem for organizations that want to make real-time decisions. Most systems today simply do not have the power or capacity to cope with the volumes of sensor-based data available today. As a result, many organizations struggle to use technology components such as NoSQL databases, streaming data systems, distributed messaging, Hadoop, and others to custom develop fusion solutions for industrial IoT.  

ThingSpan has been purpose-built to address the performance gap in reaping business insights from fast data. Its unique, object- and relationship-oriented approach groups data into objects to enable much faster processing as well as rapid navigation of complex queries. ThingSpan ensures superior performance by organizing data about people, locations, events, and devices, into real-world objects. 

Objectivity’s ThingSpan incorporates three key attributes that set it apart from any other solution in the industry. These include:

  • A dramatically improved sensor-to-insight data flow for customers involved in industrial IoT
  • A simpler, faster, and better way to build, deploy, and manage advanced information fusion solutions
  • A reference architecture base (or foundation) that leverages key open sources efforts – Spark, HDFS, YARN – to support an open system for building information solutions

Objectivity’s ThingSpan is available immediately, with additional functionality available in Q1 2016. More details on ThingSpan can be found at

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