Animated data videos have gained significant popularity in recent years. However, authoring data videos remains challenging due to the complexity of creating and coordinating diverse components (e.g., visualization, animation, audio, etc.). Although numerous tools have been developed to streamline the process, there is a lack of comprehensive understanding and reflection of their design paradigms to inform future development. To address this gap, we propose a framework for understanding data video creation tools along two dimensions: what data video components to create and coordinate, including visual, motion, narrative, and audio components, and how to support the creation and coordination. By applying the framework to analyze 46 existing tools, we summarized key design paradigms of creating and coordinating each component based on the varying work distribution for humans and AI in these tools. Finally, we share our detailed reflections, highlight gaps from a holistic view, and discuss future directions to address them.