Database systems differ from small-scale stripped database programs for embedded devices with minimal footprint to large-scale OLAP applications for server devices. For relational database management systems, two storage architectures have been introduced: the row-oriented and the column-oriented architecture. To select the optimal architecture for a certain application, we need workload information and statistics. In this paper, we present a workload representation approach that enables us to represent workloads across different DBMSs and architectures. Our approach also supports fine granular workload analyses based on database operations.
['Andreas Lübcke', 'Veit Köppen', 'Gunter Saake']
Workload Representation across Different Storage Architectures for Relational DBMS