Datacubes are enablers for analysis-ready, user-centric Big Data services in science and engineering, such as sensor data, images, image timeseries, simulations (like weather), and statistics data. The pioneer datacube engine, rasdaman, is world-wide leading according to ESA and other experts, with manifold epigons trying to copy. Rasdaman, though, stands out through its performance, scalability, flexibility, security, and standards support, plus its capability for planetary-scale peer federations, shown on Petabyte satellite and climate data, with more than 1000x cloud parallelization. Research Data Alliance in 2018 has attested that rasdaman can be 300x faster than other tools. Further, rasdaman is official datacube reference implementation and blueprint for the OGC and ISO datacube standards. In summary, rasdaman heralds a new generation of services on massive, distributed spatio-temporal data standing out through its flexibility (any query, any time), performance and scalability (2.5+ PB, 1000x parallelization), security (access control down to single pixel level), and open standards (being reference implementation).
Primary Application Area: Cyber, AI, Data, Software
Technology Development Status: Commercial Product
Technology Readiness Level: TRL 9
Vetted Programs/Awards: Winner, 2018 NATO Defense Innovation Challenge; winner, 2014 Copernicus Masters T-Systems Big Data Challenge; and a series of further innovation awards.
Organization Type: Mid-stage Startup (A or B)
Showcase Booth #: 12T
GOVT/EXTERNAL FUNDING SOURCES
External Funding to Date: European Commission, European Space Agency, German national funding: a series of research projects, see http://rasdaman.com/projects.php