Motion-based control is gaining popularity, and motion gestures form a complementary modality in human-computer interactions. To achieve more robust user independent motion gesture recognition in a manner analogous to automatic speech recognition, we need a deeper understanding of the motions in gesture, which arouses the need for a 6D motion gesture database. In this work, we present a database that contains comprehensive motion data, including the position, orientation, acceleration, and angular speed, for a set of common motion gestures performed by different users. We hope this motion gesture database can be a useful platform for researchers and developers to build their recognition algorithms as well as a common test bench for performance comparisons. Associated codes with the dataset along with instructions may be found on our GitHub page at https://github.com/olivesgatech/6DMG.