Even though systems such as Hadoop and Spark can grapple with large amounts of data, their tools for analyzing and parsing this information efficiently and in real-time are still limited. A two-year old Seattle startup called SpaceCurve will release on Tuesday a new database system aimed to speed the process of analyzing location-oriented data as it is being generated.
“We’re in a position to fuse spatial data that is very complex and difficult to work with,” said SpaceCurve CEO Dane Coyer. The software can “continuously ingest high-volume geospatial data” and allow users to query and monitor the information.
About 80 percent of data has some sort of geospatial component, IT analyst firm Gartner estimates. Yet few enterprise software tools are equipped to make the most of this data, Coyer said.
Traditional databases and even newer big data processing systems aren’t really optimized to quickly analyze such data, even though most all systems have some geospatial support. And although there are no shortage of geographic information systems, they aren’t equipped to handle the immense volumes of sensor data that could be produced by Internet-of-things-style sensor networks, Coyer said.
The SpaceCurve development team developed a set of geometric computational algorithms that simplifies the parsing of geographic data. They also built the core database engine from scratch, and designed it to run across multiple servers in parallel.
As a result, SpaceCurve, unlike big data systems such as Hadoop, can perform queries on real-time streams of data, and do so at a fraction of the cost of in-memory analysis systems such as Oracle’s TimesTen, Coyer said.
The software could have a wide range of uses, Coyer said. Telecommunications firms could use the technology to monitor the movement of their users in real time. It could also be used to manage the tsunami of incoming sensor data from remote systems.
As an example of the system’s capabilities, Coyer showed how SpaceCurve could present a real-time visual display of vehicle traffic traveling through the city of Seattle coupled with demographic summaries of the travelers, using log information from cell towers and matching that data with U.S. Census Bureau statistics.
“When you consider any kind of technology that allows you to use geographic information to optimize processes and create efficiencies, you will have a lots of use cases that have a pretty good return on investment,” said Tom Petrocelli, who is a research director covering enterprise social, mobile, and cloud applications for the analysis firm Neuralytix.
In this field, SpaceCurve’s differentiator could be the combination of the volume of data the software can handle in conjunction with its real-time analysis capabilities. A system of this sort could set the stage for large-scale mobile marketing campaigns that could let an individual know of a sale as he or she walks by the store with the items on sale, Petrocelli said.
There are no shortage of geospatial-oriented database systems and software. IBM InfoSphere Streams, for instance, also is marketed for analyzing large amounts of geospatially oriented data on the fly. Because these technologies are so new, it is too soon to determine which approach works the best, Petrocelli said.
SpaceCurve has already garnered a number of customers across different industries, including government software provider Socrata, IT performance management software provider Dyn, and geospatial analytics service provider Via Informatics.
SpaceCurve was founded in 2009 and has gotten investments from a number of different investment firms, including Reed Elsevier Ventures and Divergent Ventures. SpaceCurve has partnered with a number of IT vendors conversant in the geospatial space, including wireless services analyst AirSage, system integrator L3, and geospatial software provider Esri.
SpaceCurve did not reveal the cost of its software, though Coyer noted it is in the range of most enterprise software packages. It requires Linux and can be run on cloud infrastructure services such as Amazon’s.