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Many important business applications use complex Database Management Systems (DBMS). These DBMS have to be administrated and optimized for an optimal performance, especially in time-critical applications. Administration and optimization are very complex and costly tasks. Therefore, researchers and DBMS vendors focus on development of self-tuning techniques for a continuous adaption, e.g., the COMFORT automatic tuning project or the MAPE approach by IBM. However, the optimization and usage of self-tuning techniques for allocation and storage management of data are less investigated. DBMS vendors inform their customers about advantages and disadvantages of optimizing data storage in their user manuals and tuning guidelines. They recommend usage of functionality to optimize data storage with respect to the higher administration costs.
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