Real-time Data Infrastructure at Uber
Summary: Uber's real-time data stack: PB-scale ingestion/processing built on OSS with Uber-specific refinements to meet latency and scale. Highlights three scaling challenges per component, and real-time use cases (incentives, fraud, ML) with key lessons. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yupeng Fu (Uber)
- 2. Chinmay Soman (Uber)
BibTeX Citation
@inproceedings{fu_sigmod21,
title = {{Real-time Data Infrastructure at Uber}},
author = {Fu, Yupeng and Soman, Chinmay},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457552},
url = {https://dl.acm.org/doi/10.1145/3448016.3457552},
year = {2021}
}
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