Privacy-enhancing technologies (PETs) belong to a class of technical measures which aim at preserving the privacy of individuals or groups of individuals. Numerous PETs have been proposed for all kinds of purposes, but are difficult to be compared with each other. The challenge here lies in the fact that information privacy is a comprehensive concept with solutions being diverse, with different focus and aims. As existing taxonomies cover information security-related aspects, while neglecting privacy-specific properties, this work aims at filling this gap by describing a universal taxonomy of PETs where the taxonomy aspects are selected such that they allow the categorization of PETs in different dimensions and properties to cover a wide area of privacy (e.g., user privacy, data privacy). It provides the reader with a tool for the systematic comparison of different PETs. This helps in identifying limitations of existing PETs, complementary technologies, and potential research directions. To demonstrate its applicability, the proposed taxonomy is applied to a set of key technologies covering different disciplines such as data anonymization, privacy-preserving data querying, communication protection, and identity hiding.