This presentation focuses on the role of geospatial big data analytics tools in advancing sustainable smart cities. It emphasizes that achieving United Nations Sustainable Development Goals (SDGs) related to sustainable cities, clean energy, industry, innovation, and climate action can be facilitated by effectively implementing the smart city concept, which relies on location-based data and technologies like big data, Geographic Information Systems (GIS), cloud computing, and the Internet of Things (IoT). The research delves into the practical application of these tools, particularly Dask-GeoPandas and Apache Sedona, for handling geospatial big data in the context of smart cities. Performance comparisons reveal that these cluster computing systems outperform traditional methods, providing faster and more efficient data handling, which is essential for urban management in smart cities. The talk also highlights the advantages of the GeoParquet data format, which is faster and more compact than other formats like GPKG. Additionally, the presentation emphasizes the significance of open data sources, such as Energy Performance Certificates (EPC) data and mapping data, in analyzing the energy efficiency of domestic buildings, aligning with net zero carbon emission goals. By leveraging geospatial big data analytics tools, cities can effectively manage urban infrastructure and buildings while advancing sustainability and energy efficiency objectives. This study underscores the potential of these tools for smart infrastructure and buildings and suggests that future research could explore larger spatial datasets and cloud-native platforms to further test their capabilities.