DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System
Summary: DOP-SQL is a general-purpose differentially private SQL engine supporting selection, projection, aggregation, joins, and GROUP BY. It integrates down-neighborhood-optimal mechanisms for state-of-the-art utility and is extensible beyond its PostgreSQL implementation. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Jianzhe Yu (Hong Kong University of Science and Technology)
- 2. Wei Dong (Hong Kong University of Science and Technology)
- 3. Juanru Fang (Hong Kong University of Science and Technology)
- 4. Dajun Sun (Hong Kong University of Science and Technology)
- 5. Ke Yi (Hong Kong University of Science and Technology)
BibTeX Citation
@article{yu_vldb24,
title = {{DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System}},
author = {Yu, Jianzhe and Dong, Wei and Fang, Juanru and Sun, Dajun and Yi, Ke},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4385--4388},
doi = {10.14778/3685800.3685881},
url = {https://doi.org/10.14778/3685800.3685881},
year = {2024}
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 64 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00038522486 |
| 276 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB | 0.0002234348 |
| 1,166 | PrivateSQL: A Differentially Private SQL Query Engine | 2019 | VLDB | 0.00011731286 |
| 4,496 | R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys | 2022 | SIGMOD | 6.5764614e-05 |
| 6,661 | Better than Composition: How to Answer Multiple Relational Queries under Differential Privacy | 2023 | SIGMOD | 5.717454e-05 |
| 6,803 | Residual Sensitivity for Differentially Private Multi-Way Joins | 2021 | SIGMOD | 5.6783493e-05 |
| 8,334 | Continual Observation of Joins under Differential Privacy | 2024 | SIGMOD | 5.3527996e-05 |
| 11,685 | Universal Private Estimators | 2023 | PODS | 4.9793485e-05 |
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