Based on the current evolution in computer hardware architectures, main memory plays an increasing important role for modern database systems. To fully leverage the performance properties of main memory, database systems need to be aware of the properties of enterprise applications. Therefore I will show some analysis of enterprise applications and their data usage and how this can affect the database layer. Current database systems lack features that optimize the physical storage engine based on the workload of the applications (without replication) due to the high cost of rearranging the data on disk. Using our research prototype - HYRISE - I present a system that depending on the input workload allows selecting an optimal vertical partitioning for the tables of the application. To validate the approach we used an adapted application benchmark.
Since modern enterprise applications will evolve faster then the previous generations it becomes more important to track changes of the workload and provide a high-performance algorithm to adapt to changes. As an outcome we will present an adapted version of our initial algorithm that allows incremental calculating of the optimal layout to reduce the overall search space.