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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2307.06621 |
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| _version_ | 1866929467061960704 |
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| author | Powałka, Leon Poon, Chris Xia, Yitong Meines, Siebren Yan, Lan Cai, Yuduan Stavropoulou, Gina Dukai, Balázs Ledoux, Hugo |
| author_facet | Powałka, Leon Poon, Chris Xia, Yitong Meines, Siebren Yan, Lan Cai, Yuduan Stavropoulou, Gina Dukai, Balázs Ledoux, Hugo |
| contents | When it comes to storing 3D city models in a database, the implementation of the CityGML data model can be quite demanding and often results in complicated schemas. As an example, 3DCityDB, a widely used solution, depends on a schema having 66 tables, mapping closely the CityGML architecture. In this paper, we propose an alternative (called cjdb) for storing CityGML models efficiently in PostgreSQL with a much simpler table structure and data model design (only 3 tables are necessary). This is achieved by storing the attributes and geometries of the objects directly in JSON. In the case of the geometries we thus adopt the Simple Feature paradigm and we use the structure of CityJSON. We compare our solution against 3DCityDB with large real-world 3D city models, and we find that cjdb has significantly lower demands in storage space (around a factor of 10), allows for faster import/export of data, and has a comparable data retrieval speed with some queries being faster and some slower. The accompanying software (importer and exporter) is available at https://github.com/cityjson/cjdb/ under a permissive open-source license. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_06621 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | cjdb: a simple, fast, and lean database solution for the CityGML data model Powałka, Leon Poon, Chris Xia, Yitong Meines, Siebren Yan, Lan Cai, Yuduan Stavropoulou, Gina Dukai, Balázs Ledoux, Hugo Databases When it comes to storing 3D city models in a database, the implementation of the CityGML data model can be quite demanding and often results in complicated schemas. As an example, 3DCityDB, a widely used solution, depends on a schema having 66 tables, mapping closely the CityGML architecture. In this paper, we propose an alternative (called cjdb) for storing CityGML models efficiently in PostgreSQL with a much simpler table structure and data model design (only 3 tables are necessary). This is achieved by storing the attributes and geometries of the objects directly in JSON. In the case of the geometries we thus adopt the Simple Feature paradigm and we use the structure of CityJSON. We compare our solution against 3DCityDB with large real-world 3D city models, and we find that cjdb has significantly lower demands in storage space (around a factor of 10), allows for faster import/export of data, and has a comparable data retrieval speed with some queries being faster and some slower. The accompanying software (importer and exporter) is available at https://github.com/cityjson/cjdb/ under a permissive open-source license. |
| title | cjdb: a simple, fast, and lean database solution for the CityGML data model |
| topic | Databases |
| url | https://arxiv.org/abs/2307.06621 |