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 50 of 52 citing papers.
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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