Schema Evolution

Schema Evolution is a data management method that enables the controlled modification of a database schema over time to accommodate changing data requirements while preserving data integrity and ensuring backward compatibility in systems such as data lakehouses, data warehouses, and data pipelines.

292

Publications

13.2K

Citations

650

Authors

263

Institutions

Publications per year

2017–2026

30

Authors

650

  1. MK
    Meike Klettke

    University of Rostock, Germany

    10 publications · 230 citations

    10

    h-index

  2. CZ
    Carlo Zaniolo

    University of California, Los Angeles, United States

    9 publications · 636 citations

    9

    h-index

  3. CC
    Carlo Curino

    Microsoft (United States), United States

    8 publications · 622 citations

    8

    h-index

  4. HJ
    Hyun Jin Moon

    NEC (United States), United States

    8 publications · 622 citations

    8

    h-index

  5. PA
    Philip A. Bernstein

    Microsoft (United States), United States

    7 publications · 266 citations

    7

    h-index

1–5 of 650

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 15 publications · 725 citations

    12

    h-index

  2. Data & Knowledge Engineering

    DKE · 8 publications · 363 citations

    8

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 8 publications · 536 citations

    8

    h-index

  4. ACM SIGMOD Record

    7 publications · 581 citations

    7

    h-index

  5. Information Systems

    6 publications · 206 citations

    6

    h-index

1–5