rasdaman ("raster data manager") allows management and analytics of massive multidimensional arrays ("datacubes") such as sensor, image, simulation, and statistics data appearing in domains like Earth, Space, and Life sciences. In particular its flexibility, performance, scalability, and support for open standards make rasdaman stand out.
From simple geo imagery services up to complex analytics, rasdaman provides the whole spectrum of functionality on spatio-temporal raster data - on regular and irregular grids, accessible through your well-known clients, from Leaflet over NASA WorldWind and QGIS to R and Python.
Actionable datacubes from the inventors who pioneered Array Databases. Much has happened since then - see the latest news for what is going on lately in the rasdaman and standardization universe!
It's easy! Just go to the datacube playground. Or download Debian packages, or - of course - the source code. For each step, there is ample documentation available, as well as professional support, including dedicated mailing lists. To cite rasdaman please usehttps://doi.org/10.5281/zenodo.1040170 !
Independent experts unanimously attested that rasdaman "significantly transforms the way scientists access and use data in a way that hitherto was not possible". A series of international innovation awards recognizes rasdaman's lead in datacube analytics services. US CIO Review has picked rasdaman into their Most Promising Big Data Technologies, etc.
The rasdaman team proudly contributes to the open-source community - rasdaman is OSGeo community project and part of the OSGeo Live DVD of particularly recommended open-source geo tools.
Based on its unparalleled experience the rasdaman team is leading Big Datacube standardization in OGC and ISO shaping and driving the coverage and SQL datacube standards, often chairing the groups. The rasdaman array query language forms the blueprint for the ISO Array SQL and OGC WCPS datacube analytics standards.