We extend YAGO2 with geospatial information represented by geometries (e.g., lines, polygons, multipolygons, etc.) encoded by Open Geospatial Consortium standards. The new geospatial information comes from official sources such as the administrative divisions of countries but also from volunteered open data of OpenStreetMap. The resulting knowledge graph is currently the richest in terms of geospatial information publicly available, open source, knowledge graph.

The volume of available spatial data that is generated and collected has significantly increased in the last few years. A number of applications based on Map-Reduce-like systems and cloud infrastructure have emerged. These applications offer a variety of features, however they differ in terms of spatial functions, partitioning and indexing. In this paper we present our own implementation that enables spatial support for distributed execution of spatial SQL queries as part of the system Exareme. Then, we evaluate some of the State-of-the-Art existing geospatial distributed systems, emphasizing on systems based on Apache Spark. We conduct detailed functional and performance benchmarks that include corner cases that stress the systems in comparison and reveal their advantages and weaknesses in both functionality and performance.