Managing tens of thousands of Database-as-a-Service instances presents significant challenges in fine-tuning their configurations to optimize database workload performance. Since individually tuning each instance is impractical, DBAs typically rely on universal, one-for-all configuration templates, which often fail to meet the specific requirements of certain instances. In this paper we explore methods that DBAs could use to automatically divide the Database-as-a-Service instances into a small, manageable number of clusters with similar performance-to-configuration profiles. In this way, each group could share a single configuration template to maximize performance of its instances. We investigate whether such Database-as-a-Service instance clustering can be based solely on workload query frequencies. We validate our approach through an extensive set of experiments.