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OpenMLDB: A Real-Time Relational Data Feature Computation System for Online ML

Summary: Unified offline-online feature computation via a single plan; ensures consistency and lowers deployment cost. Low-latency online execution; pre-aggregation for fast responses; compact time-series format and stream indexing enable real-time features. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7171
Venue
SIGMOD
Year
2025
Pagerank
5.093636e-05
Overall Rank
10,696 | 26.62%
DOI
10.1145/3722212.3724446

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Authors

BibTeX Citation

@inproceedings{zhou_sigmod25,
        title = {{OpenMLDB: A Real-Time Relational Data Feature Computation System for Online ML}},
        author = {Zhou, Xuanhe and Zhou, Wei and Qi, Liguo and Zhang, Hao and Chen, Dihao and He, Bingsheng and Lu, Mian and Li, Guoliang and Wu, Fan and Chen, Yuqiang},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3722212.3724446},
        url = {https://dl.acm.org/doi/10.1145/3722212.3724446},
        year = {2025}
}

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