cjdb

A Simple, Fast, and Lean Database Solution for the CityGML Data Model

Conference paper (2024)

Authors

Leon Powałka Student
Chris Poon Student
Yitong Xia Student
Siebren Meines Student
Lan Yan Student
Yuduan Cai Student
G. Stavropoulou Urban Data Science - Architecture and the Built Environment
B. Dukai 3DGI
H. Ledoux Urban Data Science - Architecture and the Built Environment
Research Group
Urban Data Science (Architecture and the Built Environment) (TU Delft)
Copyright: © 2024 Leon Powałka, Chris Poon, Yitong Xia, Siebren Meines, Lan Yan, Yuduan Cai, G. Stavropoulou, B. Dukai, H. Ledoux
DOI: https://doi.org/10.1007/978-3-031-43699-4_47
3D modelling DBMS CityGML 3DCityDB CityJSON
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Published Date

2024

Language

English

Reuse Rights

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Faculty

Architecture and the Built Environment

Department

Urbanism

Research Group

Urban Data Science

Abstract

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.