Data arising in real world applications have space and t i m e dimensions that require database support. Because of this, there i s growing attention o n spatiotemporal databases. In this paper, we introduce two temporal data models extendable t o spatiotemporal data onespoint- based and temporal element-based data models. Our goal i s t o understand which data model i s less complex than the other when space dimension i s incorporated into the data models. To this end, we compare two query languages for t h e data models in spatiotemporal context - SQL and ParaSQL. Since query languages are tightly coupled t o their underlying data models, their complexity i s influenced by their data models. We use Guting's use case in our comparison and show that ParaSQL i s less complex than SQL sufice t o say that the temporal element-based data model is more user-friendly extendible to spatiotemporal data models if data has similar properties t o Guting's use case.