The intrinsic cost of causal consistency

Abstract

In the last few years, causal consistency has become a popular consistency model for geo-replicated databases. The algorithms proposed to enforce causal consistency typically associate with each operation some metadata, which is used to guarantee that an operation is not executed if its execution would break causality. This may lead to the impression that causal consistency is intrinsically costly and non scalable. In this paper, we analyze the metadata costs of enforcing causal consistency and put these costs in perspective, considering the metadata that is necessary to enforce reliability. We show that by wisely ordering the propagation of operations it is possible to enforce causal consistency without any additional metadata other than the already necessary to enforce reliability.