Producing software systems that achieve acceptable tradeoffs among multiple non-functional properties remains a significant engineering problem. We propose an approach to solving this problem that combines synthesis of spaces of design alternatives from logical specifications and dynamic analysis of each point in the resulting spaces. We hypothesize that this approach has potential to help engineers understand important tradeoffs among dynamically measurable properties of system components at meaningful scales within reach of existing synthesis tools. To test this hypothesis, we developed tools to enable, and we conducted, a set of experiments in the domain of relational databases for object-oriented data models. For each of several data models, we used our approach to empirically test the accuracy of a published suite of metrics to predict tradeoffs based on the static schema structure alone. The results show that exhaustive synthesis and analysis provides a superior view of the tradeoff spaces for such designs. This work creates a path forward toward systems that achieve significantly better tradeoffs among important system properties.