Engineering high-performance query execution engines is a challenging task. Query compilation provides excellent performance, but at the same time introduces significant system complexity, as it makes the engine hard to build, debug, and maintain. To overcome this complexity, we propose Nautilus, a framework that combines the ease of use of query interpretation and the performance of query compilation. On the one hand, Nautilus provides an interpretation-based operator interface that enables engineers to implement operators using imperative C++ code to ensure a familiar developer experience. On the other hand, Nautilus mitigates the performance drawbacks of interpretation by introducing a novel trace-based, multi-backend JIT compiler that translates operators into efficient code. As a result, Nautilus bridges the gap between compilation and interpretation and provides the best of both worlds, achieving high performance without sacrificing the productivity of engineers.

Data management systems will face several new challenges in supporting IoT applications during the coming years. These challenges arise from managing large numbers of heterogeneous IoT devices and require combining elastic cloud and fog resources in unified fog-cloud environments. In this demonstration, we introduce a smart city simulation called IoTropolis and use it to create interactive eHealth and Smart Grid application scenarios. We use these scenarios to showcase three key challenges of unified fog-cloud environments. Furthermore, we demonstrate how our recently proposed data management system for the IoT NebulaStream addresses these challenges. Visitors to our demonstration can configure and interact with the scenarios to manage electricity usage in IoTropolis or to distribute patients across different hospitals. Thereby, visitors can actively engage with the challenges showcased by IoTropolis and utilize NebulaStream to address them. As a result, our demonstration enables visitors to experience data management for future IoT applications.