Effective Data Versioning for Collaborative Data Analytics
Summary: OrpheusDB extends a relational DB to version, store, and recreate dataset versions for collaborative analytics. Relaxes SQL, schema, and from-scratch needs with a general versioned-data query language, storage-agnostic formats, and lineage inference across existing repos. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Silu Huang (Microsoft)
BibTeX Citation
@inproceedings{huang_sigmod20,
title = {{Effective Data Versioning for Collaborative Data Analytics}},
author = {Huang, Silu},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3394027},
url = {https://dl.acm.org/doi/10.1145/3318464.3394027},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,349 | Principles of Dataset Versioning: Exploring the Recreation/Storage Tradeoff | 2015 | VLDB | 0.00011069122 |
| 1,946 | OrpheusDB: Bolt-on Versioning for Relational Databases | 2017 | VLDB | 9.4334506e-05 |
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