Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Causal Consistency

  • Alejandro Z. TomsicEmail author
  • Marc Shapiro
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_80812


Causal consistency (CC); Causal memory; Causal-plus consistency (Causal+ consistency, C+C)


Causal consistency is a “Data Consistency Model” (q.v.) initially introduced for message passing (distributed) systems and later for shared memory systems. It ensures that, writes are observed by every party in the system in potential-causality order.

Potential-causality order is a global partial order of operations that tracks whether some operation may be influenced (caused) by some other operation. Formally, operation u potentially causally precedes operation v or, equivalently, operation v potentially causally depends on operation u if any of the following conditions hold (For simplicity, we drop “potentially” and shorten to “causally precedes” and to “causally depends” respectively. Similarly, “potential-causality order” will be shortened to “causality order.”):
  1. 1.

    Thread of Execution: u and v are two operations in a single thread of execution, and operation uexecuted...

This is a preview of subscription content, log in to check access.

Recommended Reading

  1. 1.
    Ahamad M, Neiger G, Burns JE, et al. Causal memory: definitions, implementation, and programming. Distrib Comput. 1995;9(1):37–49.MathSciNetCrossRefGoogle Scholar
  2. 2.
    Attiya H, Ellen F, Morrison A. Limitations of highly-available eventually-consistent data stores. In: Proceedings of the ACM SIGACT-SIGOPS 34th Symposium on the Principles of Distributed Computing; 2015. p. 385–94.Google Scholar
  3. 3.
    Du J, Iorgulescu C, Roy A, et al. GentleRain: cheap and scalable causal consistency with physical clocks. In: Proceedings of the 5th ACM Symposium on Cloud Computing; 2014. p. 4:1–4:13.Google Scholar
  4. 4.
    Lamport L. Time, clocks, and the ordering of events in a distributed system. Commun ACM. 1978;21(7):558–65.zbMATHCrossRefGoogle Scholar
  5. 5.
    Lloyd W, Freedman MJ, Kaminsky M, et al. Don’t settle for eventual: scalable causal consistency for wide-area storage with COPS. In: Proceedings of the 23rd ACM Symposium on Operating System Principles; 2011. p. 401–16.Google Scholar
  6. 6.
    Mahajan P, Alvisi L, Dahlin M. Consistency, availability, and convergence. Technical Report UTCS TR-11-22, Department of Computer Science, The University of Texas at Austin. Austin; 2011.Google Scholar
  7. 7.
    Zawirski M, Preguiça N, Duarte S, et al. Write fast, read in the past: causal consistency for client-side applications. In: Proceedings of the ACM/IFIP/USENIX 14th International Middleware Conference; 2015. p. 75–87.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Sorbonne-Universités-UPMC-LIP6ParisFrance
  2. 2.Inria ParisParisFrance