Objectivity's ThingSpan to Support Intel TAP for Fast IoT Analytics

Objectivity, which recently introduced ThingSpan, a purpose-built information fusion platform intended to simplify and accelerate companies’ ability to deploy and derive value from industrial Internet of Things (IoT) applications, announced plans to support Intel’s TAP (Trusted Analytics Platform) at Strata + Hadoop World, in NYC.

ThingSpan is aimed at helping companies “that are drowning in data but thirsty for answers in time” said Jay Jarrell, CEO and president of Objectivity, during an interview at the conference.

“We are one of Intel’s key partners within that stack which is for the Internet of Things. We are going to be a key contributor to that with regard to our scale-out metadata store, which is part of the ThingSpan new offering,” said Jarrell.  “ThingSpan is an ‘information fusion’ platform. It enriches a lot of the big data, the Hadoop 2.0 data, and correlates it with all of the new fast data – the sensor, time series-based data. We are that unique fusion platform based on our core competency of the rich heritage in object modeling. It is a great way to take lots of different data types, whether it be big data,  unstructured data, structured data, for example in Oracle,  and cross-correlate the different relationships or connections, store that in objects and then use that as the metadata, and shape new context data, and bring in the fast data. You need that correlation engine that is really fast, not only for storing data but also the relationships. That is what we are really good at.”

With the growth in the deployment of massive sensor networks, organizations have been facing challenges getting Industrial Internet of Things (IoT) applications into production. Jarrell cited a recent report from McKinsey & Company on IoT stated that in many industries, less than 1% 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 $11.1 trillion per year by 2025 through improved productivities.

ThingSpan is a purpose-built information fusion platform that simplifies and accelerates an organization's ability to deploy Industrial IoT applications. It is a massively scalable distributed platform 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 decades of developing and supporting mission-critical applications and deep domain expertise in fast data fusion, Objectivity’s object and relational oriented platforms have been “battle-tested” at scale and enterprise hardened deployments with Global 1000 customers and partners, including U.S. government organizations and defense contractors, said Jarrell. 

ThingSpan runs natively on Hadoop and plugs into the Spark ecosystem so Objectivity can leverage all the things that are going on with Kafka, and in effect the extensible architecture, added Jin H. Kim, who joined Objectivity in the last year as vice president of marketing and partner development.   “ThingSpan is taking some of the best practices in the fusion methodology and how Objectivity’s technology has been used to deliver complex national security fusion products that has been running  in fail-safe mode for more than 10 years.”

By combining native support for major open source initiatives such as HDFS, YARN, Spark, and Kafka, ThingSpan takes Objectivity’s experience and technology and packages it in a consumable form, delivering a solution that helps organizations reduce the cost, risk and time associated with building applications that leverage fast moving IoT data. “We sit between the streams coming in and the big data people like Intel stack,” said Kim.

“Our core competency goes to the unique and competitive advantage of enriching and unifying fast data worlds with the big data worlds but also enriching the metadata, the context, doing that very quickly and serving that up to the application layer in near-real-time or what we call ‘in time’ for an analyst that is making a decision,” said Jarrell.

Objectivity has been growing aggressively, said Kim, and there are plans in place for additional partnerships and integrations. “We believe we are going to be that unique component provider to enrich and bring forth a lot of the relationships and metadata in a near-real-time or in-time fashion,” said Jarrell.

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