  We present a record-breaking result and lessons learned in practicing
TPCx-IoT benchmarking for a real-world use case. We find that more system
characteristics need to be benchmarked for its application to real-world use
cases. We introduce an extension to the TPCx-IoT benchmark, covering
fundamental requirements of time-series data management for IoT infrastructure.
We characterize them as data compression and system scalability. To evaluate
these two important features of IoT databases, we propose IoTDataBench and
update four aspects of TPCx-IoT, i.e., data generation, workloads, metrics and
test procedures. Preliminary evaluation results show systems that fail to
effectively compress data or flexibly scale can negatively affect the
redesigned metrics, while systems with high compression ratios and linear
scalability are rewarded in the final metrics. Such systems have the ability to
scale up computing resources on demand and can thus save dollar costs.
