PrivateSQL: A Differentially Private SQL Query Engine
Summary: PrivateSQL is an end-to-end differentially private SQL engine for multi-relational schemas, accounting for foreign-key constraints and selectively protected entities. Workload-tuned private multi-view synopses provide accurate counting queries under a fixed privacy budget. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ios Kotsogiannis (Duke University)
- 2. Yuchao Tao (Duke University)
- 3. Xi He (University of Waterloo)
- 4. Maryam Fanaeepour (Duke University)
- 5. Ashwin Machanavajjhala (Duke University)
- 6. Michael Hay (Colgate University)
- 7. Gerome Miklau (University of Massachusetts Amherst)
BibTeX Citation
@article{kotsogiannis_vldb19,
title = {{PrivateSQL: A Differentially Private SQL Query Engine}},
author = {Kotsogiannis, Ios and Tao, Yuchao and He, Xi and Fanaeepour, Maryam and Machanavajjhala, Ashwin and Hay, Michael and Miklau, Gerome},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {11},
pages = {1371--1384},
doi = {10.14778/3342263.3342274},
url = {https://doi.org/10.14778/3342263.3342274},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 53 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,989 | Practical Security and Privacy for Database Systems | 2021 | SIGMOD | 4.9793485e-05 |
| 12,016 | ATLANTIC: Making Database Differentially Private and Faster with Accuracy Guarantee | 2021 | VLDB | 4.9793485e-05 |
| 12,028 | Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration | 2021 | VLDB | 4.9793485e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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