Causal Consistency and Latency Optimality: Friend or Foe?

Causal consistency is an attractive consistency model for replicated data stores. It is provably the strongest model that tolerates partitions, it avoids the long latencies associated with strong consistency, and, especially when using read-only transactions, it prevents many of the anomalies of weaker consistency models. Recent work has shown that causal consistency allows "latency-optimal" read-only transactions, that are nonblocking, single-version and single-round in terms of communication. On the surface, this latency optimality is very appealing, as the vast majority of applications are assumed to have read-dominated workloads. In this paper, we show that such "latency-optimal" read-only transactions induce an extra overhead on writes, the extra overhead is so high that performance is actually jeopardized, even in read-dominated workloads. We show this result from a practical and a theoretical angle. First, we present a protocol that implements "almost laten- cy-optimal" ROTs but does not impose on the writes any of the overhead of latency-optimal protocols. In this protocol, ROTs are nonblocking, one version and can be configured to use either two or one and a half rounds of client-server communication. We experimentally show that this protocol not only provides better throughput, as expected, but also surprisingly better latencies for all but the lowest loads and most read-heavy workloads. Then, we prove that the extra overhead imposed on writes by latency-optimal read-only transactions is inherent, i.e., it is not an artifact of the design we consider, and cannot be avoided by any implementation of latency-optimal read-only transactions. We show in particular that this overhead grows linearly with the number of clients.