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In this work we present novel query evaluation techniques for data integration systems in different environments, ranging from a central data-warehouse approach, over distributed virtual market places, to peer-to-peer (P2P) systems. Based on a new distributed evaluation technique, the so-called HyperQueries, we present a reference architecture for distributed virtual market places. These HyperQueries enable us to dynamically construct query evaluation plans by referencing sub-plans in the Internet. Furthermore, the process of data integration is structured. Subsequently, we investigate P2P data integration systems without central instances. We introduce so-called Super-Peers which structure a P2P network. Using this Super-Peer based network we "unroll" queries. This allows us to execute even user-defined operators nearby the data sources. Finally, we propose novel, efficient join algorithms for decision support queries in central data-warehouse systems. The proposed order-preserving hashjoins and generalized hashteams are based on early sorting and early partitioning of the inputs and can speed up the query evaluation up to orders of magnitutes.