Parallel Database Processing

Parallel Database Processing is a database processing approach that belongs to the class of parallel computing techniques, distinguished by its decomposition of database operations into concurrent tasks executed across multiple processors or nodes to enhance query performance and data throughput.

264

Publications

16.4K

Citations

594

Authors

179

Institutions

Publications per year

2017–2026

14

Authors

594

  1. DJ
    David J. DeWitt

    University of Wisconsin–Madison, United States

    20 publications · 4.3K citations

    18

    h-index

  2. PV
    Patrick Valduriez

    Institut national de recherche en sciences et technologies du numérique, France

    9 publications · 639 citations

    9

    h-index

  3. OF
    Ophir Frieder

    Illinois Institute of Technology, United States

    8 publications · 163 citations

    8

    h-index

  4. JG
    Jim Gray

    Microsoft (United States), United States

    6 publications · 1.9K citations

    6

    h-index

  5. SG
    Shahram Ghandeharizadeh

    University of Southern California, United States

    5 publications · 781 citations

    5

    h-index

1–5 of 594

Venues

  1. ACM SIGMOD Record

    16 publications · 694 citations

    13

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 14 publications · 1.1K citations

    12

    h-index

  3. Very Large Data Bases

    Conference · 10 publications · 478 citations

    10

    h-index

  4. ACM Transactions on Database Systems

    TODS · 7 publications · 596 citations

    7

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 5 publications · 853 citations

    5

    h-index

1–5