Geospatial big data use cases have become a major hot spot of analytics due to the explosion of geospatial data from sensor, smart phone, social media, transportation and geographic information system (GIS) data.
MapD enables ultra-fast querying, visualization and analysis of both spatial and non-spatial data at dramatically faster speeds than traditional systems.
The first area where traditional geospatial platforms fail is with visualizing mass amounts of geospatial data. Whether due to legacy CPU rendering or network “gaps” between server and client, traditional tools fall over when faced with even moderate (read tens of thousands of points) sized datasets.
Compare that to MapD, which, when needed can not only run the necessary query over the data but leverage the native graphics pipeline of the GPUs to render the result without copying the data to the CPU. This allows the system to scale to rendering tens of millions of points, lines or polygons with latencies measured in milliseconds and only requires sending the rendered result in compress PNG form to the client rather than potentially gigabytes of raw data.
The second area where geospatial platforms often fail is when required to perform numerically complex geospatial calculations at scale (potentially over billions of records). For example, merely converting modest amounts data from one geographic projection to another (an arithmetically intensive operation requiring multiple trigonometric calculations) can stop legacy systems in their tracks due to a lack of CPU horsepower. MapD, on the other hand, has tens of thousands of cores at its disposal across multiple GPUs and can perform such geospatial analytics calculations on-the-fly with little performance overhead. This approach also applies to complex calculations such as ad-hoc filters based on user-drawn polygons. By leveraging the immense computational throughput of the GPUs, users of MapD can perform such operations fully interactively and in real-time.
To see some of MapD’s geospatial prowess in action, please see our live GIS Tweetmap demo or our political donations demo - showing how MapD can render and allow interactive filtering on billions of rows of geospatial without lag.