Digital twinning has been established as one of the top ten technology trends in the last couple of years. The driver for this is the ongoing fourth industrial revolution in conjunction with the continuous technological developments in the necessary areas such as big data, Internet-of-Things (IoT), cloud computing, and artificial intelligence/machine learning (AI/ML). The goal of digital twinning is the (real-time) optimization of a physical entity based on its digital copy requiring the integration of various concepts of the above mentioned areas. To achieve this integration, various digital twin frameworks have been developed being used in a wide range of application domains. These frameworks are characterized by a high degree of flexibility, which, however, also complicates their usage. To overcome that shortcoming, we propose to design and to develop a comprehensive digital twin system that can be used out-of-the-box. In our view, such a system should be built from a data management perspective and should borrow well-established concepts from other data management systems such as database or data streaming systems.