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     Big Array Analytics 
    fast, flexible, scalable, standards-based
    ...and clients, clients, clients
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     Lightning Fast 
    through query optimization, parallelization, and modern hardware
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    any query, anytime
    on n-D sensor, image, simulation, and statistics data
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    from laptop to cloud to datacenter federations
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     Open Standards 
    supporting the Big Datacube standards (often made by us)
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    from python over QGIS and ESRI to virtual globes

Fastest Array Database
on Earth

Independent benchmarks demonstrate: the pioneer Array Database is fastest - by far: Leaving behind SciDB, Hadoop, Hive.

In collaboration with Jacobs University we successfully pioneer Array Databases since two decades. The result is Big Data technology unmatched in performance, flexibility, scalability, and data accessibility.


Shaping Big Data Standards

The rasdaman team drives Big Data standardization:


The Array Analytics Engine:
Datacubes at Your Fingertips

"The RASDAMAN product is currently the world leading environment in this domain and the standard working horse for OGC standardisation on these innovative data access interfaces" -- Guenther Landgraf, European Space Agency, January 2017

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.



rasdaman GmbH

  • Hans-Hermann-Sieling-Str. 17
              D-28759 Bremen
  • 0800-rasdaman or +49-421-6595777
  • 0800-rasdafax or +49-421-6608741
  • www.rasdaman.com

Responsible maintainer:

rasdaman GmbH
Represented by: Dr. Peter Baumann, Managing Director



All trade names and logos are property of the respective trademark owner.
Slider image credits: sliders: Shutterstock, ESA, rasdaman, template provider, rasdaman.