Startup SpaceCurve Promises Speedy Geospatial Data Analysis

January 15, 2015

The big-data field has recently seen a boom in technology that collects location-related information. The ability to quickly make good use of that data, though, has lagged behind our capacity to collect it. That gap is now being addressed, according to IT World’s piece, “Startup Rethinks Databases for the Real-Time Geospatial Era.” SpaceCurve, launched in 2009 and based in Seattle, recently released their new database system (also named “SpaceCurve”) intended to analyze geospatial data as it comes in. Writer Joab Jackson summarizes some explanatory tidbits from SpaceCurve CEO Dane Coyer:

“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.”

Jackson gives a brief rundown of ways this data can be used. Whether these examples illustrate mostly positive or negative impacts on society I leave for you, dear readers, to judge for yourselves. The piece notes that SpaceCurve can work with data that has been packaged with REST, JSON, or ArcGIS formats. The platform does require Linux, and can be run on cloud services like Amazon Web Services.

Naturally, SpaceCurve is not the only company who has noticed the niche spring up around geospatial data. IBM, for example, markets their InfoSphere Streams as able to handily analyze large chunks of such information.

Cynthia Murrell, January 15, 2015

Sponsored by ArnoldIT.com, developer of Augmentext

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