2015-oct-30: Simplified Big Data Housekeeping: New OGC
2015-oct-23: EarthServer TV Documentary Awarded at Intl. Science Film Festival
2015-oct-17: Big Data Cube Standard: SQL Standard Draft Established
2015-oct-31: ESA Conference "Big Data from Space" 2016
rasdaman ("raster data manager") is the pioneer and leading Array Analytics Engine, the next generation in scalable data services for science, engineering, and beyond. It provides agile analytics on massive multidimensional arrays, such as regular and irregular spatio-temporal grids. Its patented architecture is rigorously designed for performance and scalability, Existing databases exceed 100s of Terabytes and are going Petabyte; array queries have been split across more than 1,000 cloud nodes.
The SQL-style query language allows users to flexibly build their own data product in a "mix and match" style. The underlying engine boosts performance through strong optimizations, parallelization, and modern hardware. This innovation has effectively pioneered the field of Array Databases, and is the blueprint for several Big Data standards.
Key distinguishing features of rasdaman are its flexibility, performance, scalability, and open standards support. On such spatio-temporal sensor, image, simulation, and statistics data appearing, e.g., in earth, space, and life science applications rasdaman allows to quickly set up array-intensive services which are distinguished by their flexibility, speed, and scalability. Optionally, rasdaman integrates itself smoothly into standard databases.
A multitude of clients can access rasdaman databases, such as python, R, QGIS, and ESRI. Conversely, rasdaman can link into any existing archive and with any server-side tool, such as Hadoop. Hence, rasdaman embeds itself smoothly into any existing infrastructure.More
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Slider image credits: sliders: Shutterstock, ESA, rasdaman, template provider, rasdaman.