Rasdaman ("raster data manager") has pioneered Array Databases by adding massive multi-dimensional gridded data, an information category long missing in databases, to scalable data management and analysis. Its declarative query language, rasql, extends SQL with array operators which are optimized and parallelized on server side. Installations can easily be mashed up securely, thereby enabling largescale location-transparent query processing in federations. Domain experts value the integration with their commonly used tools leading to a quick learning curve. Earth, Space, and Life sciences, but also Social sciences as well as business have massive amounts of data and complex analysis challenges that are answered by rasdaman. As of today, rasdaman is mature and in operational use on hundreds of Terabytes of timeseries datacubes, with transparent query distribution across more than 1,000 nodes. Additionally, its concepts have shaped international Big Data standards in the field, including the forthcoming array extension to ISO SQL, many of which are supported by both open-source and commercial systems meantime. In the geo field, rasdaman is reference implementation for the Open Geospatial Consortium (OGC) Big Data standard, WCS, now also under adoption by ISO.
In this tutorial we present the concepts and design rationales, and then get hands-on with real-time examples. We will run nontrivial queries both locally and via Internet, with an opportunity for participants to recap and run their own queries. Finally, we will inspect operational services.