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GeoRocket: A scalable and cloud-based data store for big geospatial files

 
: Krämer, Michel

:
Volltext urn:nbn:de:0011-n-5784347 (332 KByte PDF)
MD5 Fingerprint: e26f270f37dcd92087936eb3de32d403
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Erstellt am: 29.2.2020


SoftwareX 11 (2020), Art. 100409, 6 S.
ISSN: 2352-7110
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IGD ()
Lead Topic: Visual Computing as a Service; Research Line: Modeling (MOD); geospatial data; Big Data; distributed computing; database

Abstract
We present GeoRocket, a software for the management of very large geospatial datasets in the cloud. GeoRocket employs a novel way to handle arbitrarily large datasets by splitting them into chunks that are processed individually. The software has a modern reactive architecture and makes use of existing services including Elasticsearch and storage back ends such as MongoDB or Amazon S3. GeoRocket is schema-agnostic and supports a wide range of heterogeneous geospatial file formats. It is also format-preserving and does not alter imported data in any way. The main benefits of GeoRocket are its performance, scalability, and usability, which make it suitable for a number of scientific and commercial use cases dealing with very high data volumes, complex datasets, and high velocity (Big Data). GeoRocket also provides many opportunities for further research in the area of geospatial data management.

: http://publica.fraunhofer.de/dokumente/N-578434.html