Evaluating the differences of geographical data in relational and graph based databases
In the context of geographical information systems a lot of data is stored in databases. Since this information is often location based, the databases mostly used are "spatial databases" that offer additional optimizations and functionality to handle such data.
Location based data is highly connected and can therefore easily be interpreted as a graph. The streets within a city are an example for such data, since crossings can be thought of nodes and streets can be seen as edges. Due to this fact this kind of data should be very efficiently treated by a graph database.
The goal of this bachelor thesis is to evaluate the differences between graph based and relational databases when it comes to spatial data treatment. The advantages and disadvantages of the data storage within a graph bases database, like neo4j-spatial, have to be determined and should be compared to those of a relational spatial database like PostGIS.
Neo4J, Neo4J-Spatial, OpenStreetMap, Optimization, PostGIS, PostgreSQL, WKT