Extreme Analytics Provider MapD Debuts MapD 4.0, For Interactive Location Intelligence at Extreme Scale
New GeoSpatial Capabilities Allow Real Time Visual Exploration of Millions of Shapes and Billions of Points
SAN FRANCISCO, Calif., June 26, 2018 -- MapD Technologies, the Extreme Analytics™ platform provider, today announced the launch of MapD 4.0, a major leap forward in large-scale, interactive geospatial analytics. With native support for geospatial data tightly integrated with a powerful GPU-based rendering engine, MapD 4.0 enables unparalleled visual interactivity for large-scale location intelligence use cases, such as visually uncovering the relationship between demographic data and spending patterns on a map, uncovering driver behavior patterns from connected vehicle telemetry, and gauging cellular signal strength variances in a city, down to the block level.
“Organizations are dealing every day with a deluge of location enriched data, from always-on mobile devices, IoT enabled objects, connected vehicles, and location-stamped transactions. Many analytics tools aren’t just crumbling under the weight of data, they also lack the capabilities to handle this spatio-temporal data at granular levels. This represents a massive opportunity cost for all large businesses and government agencies,” said Venkat Krishnamurthy, Vice President of Product Management, MapD. “One of our goals for MapD 4.0, and beyond, is to overcome this problem - to give everyone, from geospatial analysts to citizen data scientists, the power to query and visualize this data in real time - for incredible new insights not possible before.”
MapD pioneered the use of massively parallel GPU processing for big data analytics in a wide range of fields, from operational and geospatial analytics to data science. Delivered in open source, cloud, and enterprise editions, MapD is ideal for use in telecom, financial services, defense and intelligence, automotive, retail, pharmaceutical, advertising, and academia.
For geospatial analysts, MapD 4.0 further expands on the power of the MapD platform by natively supporting geometry and geographic data types such as points, lines, polygons, and multipolygons, as well as key spatial operators. Combined with a newly-enhanced rendering engine, users can now query and visualize up to millions of polygons and billions of points with unprecedented speed.
MapD 4.0 helps users ask questions and explore trends that were once too large or difficult to answer. Computation-heavy challenges are now possible at extreme speed, such as identifying two cargo trucks in one area, moving in the same direction and at the same time, while calculating their speed. Similarly, for retail, city planning or marketing purposes, users can create or select a customized geographic area anywhere in the world and instantly view demographic information in that area.
"We're very excited about the speed and scale of MapD's polygon rendering and we see tremendous opportunity here to advance our own geo-based targeting of mobile advertising," said Shaheen Mojtabai, Director of Engineering at Thinknear, a division of Telenav.
Rich Sutton is VP of Geospatial at Skyhook, another MapD customer. After seeing a preview of MapD 4.0, Rich says, “The inclusion of spatial data types in MapD 4.0 opens up game-changing possibilities for Skyhook and our partners. For all current applications where we’ve abstracted complex polygonal objects to tiles or point clouds, we’ll now be able to operate directly on native geometries. This simplifies our processing supply chain and opens up huge opportunities for data analysis and enrichment.”
In addition to its expanded polygon and rendering engine improvements, MapD 4.0 offers a number of improvements for enterprise-readiness that make it easier to support machine learning, access management, and collaboration. For more about these improvements, visit the MapD blog; to learn more about MapD 4.0, see MapD’s release notes at https://www.mapd.com/docs/latest/.
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OmniSci is the pioneer in accelerated analytics. The OmniSci platform is used in business and government to find insights in data beyond the limits of mainstream analytics tools. Harnessing the massive parallelism of modern CPU and GPU hardware, the platform is available in the cloud and on-premise. OmniSci originated from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). OmniSci is funded by GV, In-Q-Tel, New Enterprise Associates (NEA), NVIDIA, Tiger Global Management, Vanedge Capital and Verizon Ventures. The company is headquartered in San Francisco. Learn more about OmniSci at www.omnisci.com