A Distributed Quorum System for Ensuring Bounded Staleness of Key-Value Stores

Modern storage systems employing quorum replication are often configured to use partial, non-strict quorums to prioritize performance over consistency. These systems return the most recently changed data item only from a set of replicas to respond more quickly to a read request without guaranteeing that the data item is the most recently changed for all of the data. Because these partial quorum mechanisms provide only basic eventual consistency guarantees, with no limit on the freshness of the data returned, sometimes these configurations are not acceptable for certain applications. In this work, we have devised a new key-value store with partial quorums while ensuring bounded staleness. Our store reports the expected bounds on staleness with respect to wall clock. We evaluated our new key-value store with Yahoo! Cloud Service Benchmarks and show its performance.

[1]  Zheng Zhang,et al.  Trading replication consistency for performance and availability: an adaptive approach , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[2]  Amin Vahdat,et al.  Design and evaluation of a conit-based continuous consistency model for replicated services , 2002, TOCS.

[3]  Werner Vogels,et al.  Dynamo: amazon's highly available key-value store , 2007, SOSP.

[4]  Heiko Schuldt,et al.  FAS - A Freshness-Sensitive Coordination Middleware for a Cluster of OLAP Components , 2002, VLDB.

[5]  Werner Vogels,et al.  Building reliable distributed systems at a worldwide scale demands trade-offs between consistency and availability. , 2022 .

[6]  Robert H. Thomas,et al.  A Majority consensus approach to concurrency control for multiple copy databases , 1979, ACM Trans. Database Syst..

[7]  William H. Sanders,et al.  An Adaptive Quality of Service Aware Middleware for Replicated Services , 2003, IEEE Trans. Parallel Distributed Syst..

[8]  Michel Raynal,et al.  Timed consistency for shared distributed objects , 1999, PODC '99.

[9]  Ion Stoica,et al.  Probabilistically Bounded Staleness for Practical Partial Quorums , 2012, Proc. VLDB Endow..

[10]  David K. Gifford,et al.  Weighted voting for replicated data , 1979, SOSP '79.

[11]  Jonathan Goldstein,et al.  Relaxed currency and consistency: how to say "good enough" in SQL , 2004, SIGMOD '04.

[12]  Amin Vahdat,et al.  The costs and limits of availability for replicated services , 2006 .

[13]  Nancy A. Lynch,et al.  Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services , 2002, SIGA.

[14]  Jessica K. Hodgins,et al.  Temporal notions of synchronization and consistency in Beehive , 1997, SPAA '97.