Many databases today capture both, structured and unstructured data. Making use of such hybrid data has become an important topic in research and industry. The efficient evaluation of hybrid data queries is the main topic of this thesis. Novel techniques are proposed that improve the whole processing pipeline, from indexes and query optimization to run-time processing. The contributions are evaluated in extensive experiments showing that the proposed techniques improve upon the state of the art.
query optimizationgraph-structured datardfsemantic webindexes