genehmigten Dissertation.

Analytical query processing in database systems aims at providing the requested infor-mation within an acceptable response time while affecting the performance of concurrently executed transactional workloads as little as possible. Scalability in the context of ana-lytical query processing refers to the ability of the database system to process highly data intensive and complex queries efficiently and to take advantage of additional resources to improve query execution performance. In order to achieve the goal of scalable analytical query processing, we examine the following three approaches, which focus on response time, robustness, and resource utilization of analytical queries. First, we focus on synergy-based workload management for exploiting synergies be-tween a multitude of analytical queries, which are executed concurrently. The knowledge of the synergies among queries for a given workload allows to process them in an efficient way with respect to our goals. E.g., for caching synergies, by executing queries reading the same data in parallel, we minimize the buffer pool requirements as well as the I/O time of these queries. Based on the fact that both, positive and negative synergies, ar