Data Consistency Models

Data Consistency Models is a formal framework within data lakehouse architecture that specifies the rules and mechanisms governing the accuracy, timeliness, and uniformity of data across distributed systems, distinguishing it from other data management primitives by its focus on ensuring coherent and dependable data states during concurrent read and write operations.

152

Publications

18.6K

Citations

412

Authors

178

Institutions

Publications per year

2017–2026

30

Authors

412

  1. AG
    Alexey Gotsman

    IMDEA Software Institute, Spain

    5 publications · 226 citations

    5

    h-index

  2. SV
    Sarita V. Adve

    University of Illinois Urbana-Champaign, United States

    4 publications · 1.4K citations

    4

    h-index

  3. JM
    Joseph M. Hellerstein

    University of California, Berkeley, United States

    4 publications · 294 citations

    4

    h-index

  4. WZ
    Willy Zwaenepoel

    Rice University, United States

    3 publications · 164 citations

    3

    h-index

  5. DT
    Doug Terry

    Palo Alto Research Center, United States

    3 publications · 427 citations

    3

    h-index

1–5 of 412

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 5 publications · 139 citations

    5

    h-index

  2. Communications of the ACM

    4 publications · 10.2K citations

    4

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 113 citations

    3

    h-index

  4. Data & Knowledge Engineering

    DKE · 3 publications · 44 citations

    3

    h-index

  5. ACM SIGPLAN Notices

    3 publications · 46 citations

    3

    h-index

1–5