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)

Paper ID: 12019
Venue: VLDB
Year: 2019
Pagerank: 0.00011999046
Overall Rank: 1,144 | 92.16%
DOI: 10.14778/3342263.3342274

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 2 of 52 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
11,712	ATLANTIC: Making Database Differentially Private and Faster with Accuracy Guarantee	2021	VLDB	5.093636e-05
11,725	Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration	2021	VLDB	5.093636e-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.

Rank	Cited Paper	Year	Venue	Pagerank
16	MAGIC SETS AND OTHER STRANGE WAYS TO IMPLEMENT LOGIC PROGRAMS (Extended Abstract)	1986	PODS	0.00060089598
62	Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis	2009	SIGMOD	0.00038970535
123	Revealing Information while Preserving Privacy	2003	PODS	0.00031082693
130	Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release	2007	PODS	0.00030604781
281	Towards Practical Differential Privacy for SQL Queries	2018	VLDB	0.00022445849
567	Understanding Hierarchical Methods for Differentially Private Histograms	2013	VLDB	0.00016420715
596	Private Analysis of Graph Structure	2011	VLDB	0.00015926024
836	Recursive Mechanism: Towards Node Differential Privacy and Unrestricted Joins	2013	SIGMOD	0.00013715654
1,169	PrivBayes: Private Data Release via Bayesian Networks	2014	SIGMOD	0.00011838753
1,504	A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy	2014	VLDB	0.00010548904
1,583	PriView: Practical Differentially Private Release of Marginal Contingency Tables	2014	SIGMOD	0.00010292522
1,790	Publishing Graph Degree Distribution with Node Differential Privacy	2016	SIGMOD	9.7502278e-05
2,167	Optimizing error of high-dimensional statistical queries under differential privacy	2018	VLDB	9.047803e-05
2,300	Principled Evaluation of Differentially Private Algorithms using DPBench	2016	SIGMOD	8.7833594e-05
2,562	Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies	2014	SIGMOD	8.4127196e-05
4,361	ϵktelo: A Framework for Defining Differentially-Private Computations	2018	SIGMOD	6.7443476e-05
4,881	Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics	2017	SIGMOD	6.465615e-05

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