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
- 2. Janet L. Wiener
- 3. Shridhar Iyer
- 4. Anshul Jaiswal
- 5. Ran Lei
- 6. Nikhil Simha
- 7. Wei Wang
- 8. Kevin Wilfong
- 9. Tim Williamson
- 10. Serhat Yilmaz
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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