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Efficient storage of heterogeneous geospatial data in spatial databases
Journal of Big Data ( IF 8.6 ) Pub Date : 2019-11-18 , DOI: 10.1186/s40537-019-0262-8
Atle Frenvik Sveen

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.

中文翻译:

在空间数据库中高效存储异构地理空间数据

NoSQL文档存储的无模式方法是一种诱人的解决方案,用于将异构地理空间数据导入空间数据库。但是,这种方法意味着要牺牲RDBMS的好处,例如现有的集成和ACID原则。以前对文档存储和基于表的布局进行比较以存储地理空间数据比较有利于文档存储方法,但不考虑导入可细分为同质数据集的数据。在本文中,我们提出了“异构开放式地理数据存储(HOGS)”系统。HOGS是一个命令行实用程序,可自动将地理空间数据导入PostgreSQL / PostGIS数据库。开发它是为了比较遵循ACID原则的传统存储布局和以NoSQL为灵感的文档存储的性能。导入并查询了包含1500万个要素的八个开放式地理空间数据集,以比较两个存储布局之间的差异。给出了定量实验的结果,结果表明,使用基于表的布局,使用传统的RDBMS可以存储大量开放的地理空间数据,而不会造成任何性能损失。
更新日期:2019-11-18
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