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