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Objectivity case study

Objectivity ThingSpan on Microsoft Azure delivers new data intelligence

Discovering connections in massive amounts of data

Organizations struggle to effectively use data from sensors and other streaming data sources for real-time analysis. Many apps rely on batch processing, which can require hours to days to get the required results.

ThingSpan enables greater flexibility and scalability

Objectivity’s ThingSpan on Microsoft Azure dramatically improves sensor-to-insight data flow by storing and organizing metadata. The solution delivers performance and scalability for beyond-petabyte data volumes.

Delivering new data intelligence and faster time to market

By running Objectivity’s ThingSpan on Azure, users can upload their data and start running an application within hours. Running on Azure also significantly reduces hardware costs and simplifies ThingSpan licensing.

Objectivity helps organizations discover unknown connections in data

Objectivity is a privately held software company based in San Jose, California. Since 1988, Objectivity’s software has enabled military, government agencies, and enterprise customers to develop and deploy high-performance, massively scalable analytics, data and sensor fusion, and decision support solutions. Objectivity’s mission is to help the government and enterprises deliver systems and applications that discover unknown connections in data in order to save money, eliminate downtime, or save lives in critical missions.

The continually increasing number of connected devices, systems, and users generates more data than ever before, and organizations are learning the relationships between data points are often more valuable than the data itself. For example, real-time data analysis is critical to financial services companies to prevent fraud or loss or to trace the history of decision making.

ThingSpan delivers speed and scalability on Microsoft Azure

Objectivity's ThingSpan on Azure analyzes the connections across multiple data sources in real-time. ThingSpan’s key benefits are its performance and pattern-finding capabilities coupled with speed and scalability. ThingSpan based applications running on Azure collect and interpret data in real time while simultaneously analyzing new information against an organization’s existing data so that there is no delay in receiving valuable insights and taking necessary actions.

“We see a big shift with our customers moving their applications to the cloud. With our ThingSpan product running on Azure, it demonstrates ThingSpan’s ability to scale as the volume of data increases, and the Azure elasticity allows systems to scale out or back to match demand and workloads. By running on Azure, our customers can get started with a simple proof of concept and then easily scale for production, which also simplifies software licensing,” said Jay Jarrell, President and CEO, Objectivity.

In a recent customer use case, Objectivity loaded ten billion call detail records to Azure while simultaneously building the graph (connecting the data) in ThingSpan in less than two hours. This demonstrates ThingSpan's ability to scale as the volume of data increases and how Azure’s elasticity allows systems to scale to match demand and workloads. The customer’s existing relational database solution could not return results in a useful timespan when querying the data beyond three degrees of separation. ThingSpan can process queries with up to ten degrees of separation and beyond in seconds.

“Objectivity’s ThingSpan is a very flexible and scalable platform for data and graph analytics, and by running on Azure it is even easier for users to get started and grow with their application demands.”

—Leon Guzenda, Chief Technical Officer and Founder, Objectivity

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