Evaluation of a NoSQL Database for Storing Big Geospatial Raster Data

Nicole Hein, Jörg Blankenbach
2021 GI_FORUM - Journal for Geographic Information Science  
Database systems capable of efficiently storing geospatial data are widespread. However, recent developments in earth observation systems, remote sensing, mobile mapping, and crowd sourcing lead to large amounts of geospatial mass data that can hardly be handled efficiently with the existing solutions. Especially large geospatial raster data require novel concepts for well-organized data storage. A concept for storage of large geospatially and temporally referenced image data using the NoSQL
more » ... ph database system Neo4j as a research subject of the project "RiverView®" is introduced. New strategies and access structures have been developed to ensure the persistence and performant access to image data in Neo4j. These strategies are compared with the up-and download performance of the widespread Rasdaman array database system.
doi:10.1553/giscience2021_01_s76 fatcat:qm622gefyraexewnc4ppveqsrq