Shortly after it was �rst introduced in 2006, differential privacy became the flagship data privacy de�nition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy de�nitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original de�nition is modi�ed. These categories act like dimensions: Variants from the same category cannot be combined, but variants from different categories can be combined to form new de�nitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these de�nitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collectingexisting ones.