What is Geospatial Data?
Geospatial data is data that has explicit geographic positioning information included within it, such as a road network from a geographic information system, or a geo-referenced satellite image.
More and more data is being generated every day, and that data is becoming more and more complex, hindering our ability to garner information from that data. Conventional data base technologies are used to rows and columns. Even many of the newer ‘No SQL’ databases can handle documents with different fields or columns but cannot handle the streams of data coming from the Internet of Things (IOT). Conventional hardware has only so many threads while newer Graphical Processing Units (GPU) can provide thousands of threads.
There is a solution with a truly battle-tested, open database technology that can effectively take advantage of the Open POWER platform with up to four GPUs per system. The solution is Kinetica and it can tackle the toughest problems in areas like supply chain and marketing where you want to find patterns with geospatial data. It harnesses the power of GPUs for unprecedented performance to ingest, explore and visualize data in motion and at rest. Kinetica comes with a native geospatial and visualization pipeline for rendering large volumes of data over maps. This makes Kinetica particularly well suited for fast moving, location-based IoT data.
When we say battle-tested we mean it since this was developed for the US Army Intelligence and Security Command to help keep America safe and continues to be used today. A large retailer has used this to take an inventory application that was taking over 24 hours to complete and reduce the wall clock time by almost 75% allowing for decisions to be made the same day.
Let Flagship help you realize the capability of the POWER architecture with Kinetica for your difficult, geospatial data problem without breaking the bank. Our team of consultants is ready to provide you with a consultative approach to determine if this solution fits your business. Schedule a consultation to learn more.
If you liked this blog, you might also like: What’s “Good Enough” for Linux Databases?
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