The recent proliferation of decentralized distributed hash table (DHT) proposals suggests a need for DHT benchmarks, both to compare existing implementations and to guide future innovation. We argue that a DHT-based query engine provides a unified framework for describing workloads and faultloads, injecting them into a DHT, and recording and analyzing the observed system behavior. To illustrate this argument, we describe the possibilities and challenges of using one such DHT database engine, PIER, to describe and instantiate network dataflow patterns, and to measure and report the resulting system performance. Together, these capabilities form the foundation of a benchmarking tool, while the distributed tracing and analysis facilities alone support debugging.