Objectivity Introduces ThingSpan, an Information Fusion Platform to Enrich Big Data with Fast Data

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Objectivity_LogoObjectivity, Inc., a pioneer in high-performance distributed object-oriented database technology, 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 platform 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 the deployment of massive sensor networks, organizations have been facing challenges getting Industrial IoT applications into production. As a result, most organizations struggle to effectively use data from sensors and other streaming sources in their business operations. A recent report from McKinsey & Company on 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 a positive impact of up to $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 mission-critical applications involving the most complex data sources. Over the last several years, Objectivity has been working with leading systems integrators and organizations to build and deploy advanced data and information fusion applications,” says Jay Jarrell, CEO of Objectivity. “ThingSpan is a new approach based on our experience to enable organizations to quickly and easily gain actionable insights from their Fast Data. Our goal is to help our customers accelerate time-to-production of fusion applications by providing key capabilities in the form of an information fusion platform.”

Fast Data differs from other data in that it is generated in high volume and its value is time-sensitive. However, most systems today simply do not have the power or capacity to cope with the increasing volumes of sensor-based Fast Data available to make real-time decisions. As a result, many organizations struggle to use technology components such as NoSQL databases, streaming data systems, distributed messaging, Hadoop, and others to custom-build fusion solutions for the Industrial IoT.

With decades of experience supporting mission-critical applications and a deep domain expertise in Fast Data fusion, Objectivity’s object- and relationship-oriented platforms are proven at scale and enterprise-hardened by Global 1000 customers and partners. This expertise has been infused for the first time in ThingSpan. Combined with native support for major open source initiatives like HDFS, YARN, Spark, and Kafka, ThingSpan finally delivers the solution that Industrial IoT industry leaders need in order to gain real-time insight into their data streams.

ThingSpan focuses on providing the pieces necessary in a platform to easily build and deploy production information fusion applications,” said Jin Kim, vice president of Marketing and Partner Development for Objectivity. “In order to unlock the transformative potential of the Industrial IoT, Fast Data must be harnessed in an easier to consume form. ThingSpan delivers that power to any enterprise today by leveraging both our technology competence and those of major open source initiatives.”

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 by organizing data about people, locations, events, and devices around object- and association-oriented approach.
  • A simpler, faster, and better way to build, deploy and manage advanced information fusion solutions through Spark-based abstraction
  • A reference architecture base (or foundation) that leverages key open source efforts – Spark, HDFS, YARN – to support an open system for building information solutions.


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