Saturn: a Distributed Metadata Service for Causal Consistency

Abstract

This paper presents the design, implementation, and evaluation of Saturn, a metadata service for geo-replicated systems. Saturn can be used in combination with several distributed and replicated data services to ensure that remote operations are made visible in an order that respects causality, a requirement central to many consistency criteria. Saturn addresses two key unsolved problems inherent to previous approaches. First, it eliminates the tradeoff between throughput and data freshness, when deciding what metadata to use for tracking causality. Second, it enables genuine partial replication, a key property to ensure scalability when the number of geo-locations increases. Saturn addresses these challenges while keeping metadata size constant, independently of the number of clients, servers, data partitions, and locations. By decoupling metadata management from data dissemination, and by using clever metadata propagation techniques, it ensures that the throughput and visibility latency of updates on a given item are (mostly) shielded from operations on other items or locations. We evaluate Saturn in Amazon EC2 using realistic benchmarks under both full and partial geo-replication. Results show that weakly consistent datastores can lean on Saturn to upgrade their consistency guarantees to causal consistency with a negligible penalty on performance.