Realtime Data Processing at Facebook
Summary: Realtime data processing at Facebook handles hundreds of GB/s across pipelines, guided by five design decisions on usability, performance, fault tolerance, scalability, and correctness. Seconds-latency with a persistent message bus enables Puma, Swift, and Stylus, delivering scalable, fault-tolerant streaming and valuable design lessons. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Guoqiang Jerry Chen (Meta)
- 2. Janet L. Wiener (Meta)
- 3. Shridhar Iyer (Meta)
- 4. Anshul Jaiswal (Meta)
- 5. Ran Lei (Meta)
- 6. Nikhil Simha (Meta)
- 7. Wei Wang (Meta)
- 8. Kevin Wilfong (Meta)
- 9. Tim Williamson (Meta)
- 10. Serhat Yilmaz (Meta)
BibTeX Citation
@inproceedings{chen_sigmod16,
title = {{Realtime Data Processing at Facebook}},
author = {Chen, Guoqiang Jerry and Wiener, Janet L. and Iyer, Shridhar and Jaiswal, Anshul and Lei, Ran and Simha, Nikhil and Wang, Wei and Wilfong, Kevin and Williamson, Tim and Yilmaz, Serhat},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2904441},
url = {https://dl.acm.org/doi/10.1145/2882903.2904441},
year = {2016}
}
Incoming Citations (Sorted by Pagerank)
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