cjdb: a simple, fast, and lean database solution for the CityGML data model

TL;DR

This paper introduces cjdb, a streamlined, efficient database solution for CityGML data that simplifies schema design, reduces storage needs, and maintains competitive data retrieval performance using JSON-based storage in PostgreSQL.

Contribution

The paper presents cjdb, a novel minimalistic database schema for CityGML data, significantly reducing complexity and storage compared to existing solutions like 3DCityDB.

Findings

cjdb uses only 3 tables, simplifying schema design

cjdb reduces storage space by approximately 10 times

cjdb achieves comparable or faster data retrieval speeds

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.