Database Schema Evolution

Database Schema Evolution is the systematic process of modifying and adapting the structure of a database schema over time to meet changing data requirements, integrity constraints, and application needs while preserving data consistency and minimizing disruption to existing systems.

249

Publications

10.6K

Citations

560

Authors

218

Institutions

Publications per year

2017–2026

26

Authors

560

  1. CZ
    Carlo Zaniolo

    University of California, Los Angeles, United States

    10 publications · 657 citations

    10

    h-index

  2. HJ
    Hyun Jin Moon

    NEC (United States), United States

    9 publications · 643 citations

    9

    h-index

  3. CC
    Carlo Curino

    Microsoft (United States), United States

    9 publications · 643 citations

    9

    h-index

  4. MK
    Meike Klettke

    University of Rostock, Germany

    9 publications · 188 citations

    9

    h-index

  5. US
    Uta Störl

    University of Rostock, Germany

    7 publications · 161 citations

    7

    h-index

1–5 of 560

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 13 publications · 419 citations

    11

    h-index

  2. Data & Knowledge Engineering

    DKE · 10 publications · 420 citations

    10

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 9 publications · 613 citations

    9

    h-index

  4. ACM SIGMOD Record

    9 publications · 631 citations

    9

    h-index

  5. ACM Transactions on Database Systems

    TODS · 8 publications · 556 citations

    8

    h-index

1–5