Causal consistency is the strongest consistency model that is available in the presence of partitions and provides useful semantics for human-facing distributed services. Here, we expose its serious and inherent scalability limitations due to write propagation requirements and traditional dependency tracking mechanisms. As an alternative to classic potential causality, we advocate the use of explicit causality, or application-deﬁned happens-before relations. Explicit causality, a subset of potential causality, tracks only relevant dependencies and reduces several of the potential dangers of causal consistency.
National Science Foundation
Expeditions in Computing