Big Earth Datacube Analytics Made Easy


BigDataCube Results

The BigDataCube project has been successful in establishing powerful datacube services on CODE-DE with timeseries over Sentinel 2, Sentinel 1 GRD, and value adding sea state and wind speed, produced with DLR's SAINT tool. Close to a Petabyte of datacubes is available via OGC datacube services.

DLR, though, has decided to discontinue the rasdaman service despite its success and replace it with an initial-stage datacube prototype instead. Hence, the datacube service currently advertised on CODE-DE is NOT based on rasdaman. Among the shortcomings of that service is that it only supports WCS 1 which is deprecated since many years, known as not interoperable, and not supported by most current tools. The rasdaman engine, on the other h

BigDataCube Service & Demos

The BigDataCube service has been fully established at CODE-DE on all Sentinel 2 (L1C and L2A) products, Sentinel 1 GRD over Germany, and Sentinel 1 GRD over the North Sea (sea state and wind speed products produced with DLR's SAINT tool). Altogether, around 400 TB of data are available via OGC datacube services (WCS, WCPS, WMS).

We invite you to check out the demos for a taste of the various datacube analytics capabilities. Starting with the Jupyter notebook is recommended to get a high level overview along with a tutorial-like walk-through; while it contains some Python code, knowledge of Python is not really necessary to follow the contents.

CODE-DE Datacube Precursor Available

While CODE-DE is preparing infrastructure the CODE-DE Datacube Precursor service has been released by Constructor University and rasdaman GmbH. Based on sample Sentinel 1 and 2 timeseries it offers a rich set of OGC standards conformant access, formatting, filtering, processing, and general analytics functionality.
Update: with the availability of the CODE-DE Datacube service the precursor service has been shut down.

BigDataCube kick-off meeting

The BigDataCube project has kicked off, aiming to develop flexible and scalable services for massive spatio-temporal Earth Observation data. Project coordinator, Constructor University Bremen, invited the joint research consortium, consisting of rasdaman GmbH (Bremen) , cloudeo AG (Munich) and DLR (Deutsches Zentrum für Luft- und Raumfahrt) ...


Project brief:

Start: 01 Jan 2018
Duration: 18 months
Find us:

Under the lead of Constructor University, The BigDataCube project is developing flexible and scalable services for massive spatio-temporal Earth Observation (EO) data, offered as datacubes. This paradigm replaces the millions of EO files by a few massive multi-dimensional space/time objects, such as 3D image timeseries and 4D weather forecast cubes. This way, raster data get ready for spatio-temporal analysis in the large.

Goal of BigDataCube is to enhance access to value-adding services supporting collaboration across disciplinary and geographical boundaries for industry and research. The massively simplified Big Data handling benefits users of existing services as well as new businesses, e.g., in agro-informatics: they don't need to develop or deploy complex technology and manage all data, but can use data readily, thereby freeing resources for their core business. Hence, on the BigDataCube platform novel, specialized services can be established by third parties in a fast, flexible, and scalable manner.

Concretely, the project deploys the European Datacube engine, rasdaman, in two infrastructures:

  • The commercial hosted processing environment of cloudeo. Novel datacube access control and quota will safely handle both free and proprietary data provided by Intermap and PlanetObserver.
  • The public service of CODE-DE, the German Copernicus hub, thereby complementing the batch-oriented Hadoop service with interactive extraction and processing along the paradigm of "any query, any time, on any size". DLR Bremen will exemplarily establish a weather and ocean analytics tool based on rasdaman.

Further, CODE-DE and cloudeo services will be federated, allowing users to combine datacubes from both services without the need for downloading them first.


BigDataCube employs the multi-award-winning pioneer Array Database system, rasdaman, which enables "any query, any time, on any size" on massive n-D datacubes.

Spatio-temporal sensor, image, simulation, and statistics datacubes

Optimization, Parallelization


Heterogeneous hardware support


Internationally recognized experts are teaming up for developing the next generation of services:


The Large-Scale Scientific Information Systems research group at Constructor University has worldwide reputation in Array Databases and is actively shaping OGC, ISO, and INSPIRE datacube standards.


rasdaman GmbH is technology leader in high-performance Array Databases for serving datacubes and shaper of datacube standards, with Constructor University.


cloudeo is a leading specialist in scalable geo-infrastructure, bringing together data, software and processing power with its GeoMarketplace as one-stop shop for GeoServices.


The Maritime Safety and Security Lab of the DLR Earth Observation Center (EOC) has special expertise in EO-based near-real-time ocean condition assessment. In BigDataCube, DLR provides maritime wind and sea state products.

BigDataCube project team

Photo: Heike Hoenig (rasdaman GmbH)

The BigDataCube project team
(from left to right):

  • Stefan Wiehle (DLR)
  • Dr. Ursula Benz (cloudeo AG)
  • Dimitris Bellos (cloudeo AG)
  • Simon Tzvetanov (cloudeo AG)
  • Vlad Merticariu (Constructor University, rasdaman GmbH)
  • Dr. Sven Constructoren (DLR)
  • Brennan Bell (Constructor University)
  • Bang Pham Huu (Constructor University)
  • Dimitar Misev (Constructor University, rasdaman GmbH)
  • Prof. Dr. Peter Baumann (rasdaman GmbH, Constructor University)


Dimitar Misev (Coordinator)

  • Constructor University & rasdaman GmbH

Prof. Dr. Peter Baumann

  • Constructor University & rasdaman GmbH

Dr. Ursula Benz

  • cloudeo AG

Dr. Sven Jacobsen

  • DLR
  • Contact