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Efficient storage of heterogeneous geospatial data in spatial databases
Efficient storage of heterogeneous geospatial data in spatial databases
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Efficient storage of heterogeneous geospatial data in spatial databases
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Efficient storage of heterogeneous geospatial data in spatial databases
Efficient storage of heterogeneous geospatial data in spatial databases

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Efficient storage of heterogeneous geospatial data in spatial databases
Efficient storage of heterogeneous geospatial data in spatial databases
Journal Article

Efficient storage of heterogeneous geospatial data in spatial databases

2019
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Overview
The no-schema approach of NoSQL document stores is a tempting solution for importing heterogenous geospatial data to a spatial database. However, this approach means sacrificing the benefits of RDBMSes, such as existing integrations and the ACID principle. Previous comparisons of the document-store and table-based layout for storing geospatial data favours the document-store approach but does not consider importing data that can be segmented into homogenous datasets. In this paper we propose “The Heterogeneous Open Geodata Storage (HOGS)” system. HOGS is a command line utility that automates the process of importing geospatial data to a PostgreSQL/PostGIS database. It is developed in order to compare the performance of a traditional storage layout adhering to the ACID principle, and a NoSQL-inspired document store. A collection of eight open geospatial datasets comprising 15 million features was imported and queried in order to compare the differences between the two storage layouts. The results from a quantitative experiment are presented and shows that large amounts of open geospatial data can be stored using traditional RDBMSes using a table-based layout without any performance penalties.