Stream Data Ingestion

Stream Data Ingestion is a data ingestion method that continuously acquires and processes data in real time as it is generated, distinguishing itself from batch-oriented approaches by enabling immediate, incremental processing of data streams.

6

Publications

331

Citations

19

Authors

6

Institutions

Publications per year

2017–2026

3

Authors

19

  1. JS
    Joseph Seidel

    AT&T (United States), United States

    1 publications · 103 citations

    1

    h-index

  2. LG
    Lukasz Golab

    University of Waterloo, Canada

    1 publications · 103 citations

    1

    h-index

  3. SS
    Scott Shenker

    University of California, Berkeley, United States

    1 publications · 125 citations

    1

    h-index

  4. AN
    Apostolos N. Papadopoulos

    Aristotle University of Thessaloniki, Greece

    1 publications · 11 citations

    1

    h-index

  5. IS
    Ion Stoica

    University of California, Berkeley, United States

    1 publications · 125 citations

    1

    h-index

1–5 of 19

Venues

  1. 2021 IEEE International Conference on Big Data (Big Data)

    Conference · 1 publications · 10 citations

  2. Journal Of Big Data

    1 publications · 10 citations

1–3