Real-time Data Pipelines

Real-Time Data Pipelines is a data pipeline system that continuously ingests, processes, and delivers data with minimal latency to enable immediate analysis and decision-making, distinguished from batch-oriented pipelines by its capacity to handle streaming data in near real-time.

21

Publications

1.2K

Citations

129

Authors

52

Institutions

Publications per year

2017–2026

6

Variants

Real-time Data Pipeline

Authors

129

  1. GB
    George Brims

    University of California, Los Angeles, United States

    1 publications · 26 citations

    1

    h-index

  2. LJ
    L. J. Greenhill

    Center for Astrophysics Harvard & Smithsonian, United States

    1 publications · 16 citations

    1

    h-index

  3. ND
    Nolan Denman

    University of Toronto, Canada

    1 publications · 15 citations

    1

    h-index

  4. RP
    Richard Park

    Brigham and Women's Hospital, United States

    1 publications · 97 citations

    1

    h-index

  5. CC
    Claudio Casetti

    Politecnico di Torino, Italy

    1 publications · 24 citations

    1

    h-index

1–5 of 129

Venues

  1. Machine Vision and Applications

    2 publications · 32 citations

    2

    h-index

  2. Microprocessors and Microsystems

    MICPRO · 2 publications · 69 citations

    2

    h-index

  3. Journal of Systems Architecture

    JSA · 1 publications · 24 citations

    1

    h-index

  4. GigaScience

    1 publications · 95 citations

    1

    h-index

  5. Computer Physics Communications

    1 publications · 16 citations

    1

    h-index

1–5