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Spatial data analysis is computationally intensive. Most solutions grind to a crawl at a few million points. But recent advances in parallel computing create opportunities to challenge these computational constraints. Kinetica’s vectorized spatial function library can perform computations on the fly on massive amounts of spatial data. Matthew Brown shows us some of these capabilities…
Our sat nav gives us options of the shortest route home, or avoiding tolls or highways. But what if we want the most scenic route home, or the most well-lit? Learn how to do this using a road networks as graphs, geo-spatial features as graph networks and graph optimizations.
Kinetica recently introduced a new native Azure Marketplace experience. Now, it’s easier than ever to get started with the Database for Time and Space. With just a few clicks, you will be able to provision Kinetica from the Azure Marketplace into your Azure subscription. With the free tier (size Extra Small) and pay as you…
Geospatial data is any data that has a geographic component to it. A geographic component simply implies a location (or a set of locations) that can take the form of simple points on a map with latitude and longitude coordinates or more complex shapes that describe lines and boundaries, or even elevation. Examples could include…
Multiple Supply Demand Chain Optimization (MSDO), is a common logistical problem where there are multiple sources and sinks and you’re looking for the most optimal delivery routes.
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