Architecting a Differentially Private SQL Engine
Summary: PRIVSQL: a system architecture for differentially private SQL query answering that decomposes the engine into independently optimizable components, bridging DP algorithm design and declarative DB systems. Prototype supports richer SQL and yields up to 7000× accuracy improvement, while identifying which components are mature versus underexplored for future DB research. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ios Kotsogiannis
- 2. Yuchao Tao
- 3. Ashwin Machanavajjhala
- 4. Gerome Miklau
- 5. Michael Hay
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,519 | IncShrink: Architecting Efficient Outsourced Databases using Incremental MPC and Differential Privacy | 2022 | SIGMOD | 5.4619886e-05 |
| 7,417 | DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance | 2023 | SIGMOD | 4.7355114e-05 |
| 9,195 | DPSAaS: Multi-Dimensional Data Sharing and Analytics as Services under Local Differential Privacy | 2019 | VLDB | 4.3756951e-05 |
| 9,766 | DPXPlain: Privately Explaining Aggregate Query Answers | 2023 | VLDB | 4.2856106e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 83 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00053933811 |
| 136 | Revealing Information while Preserving Privacy | 2003 | PODS | 0.0004241101 |
| 1,446 | PrivBayes: Private Data Release via Bayesian Networks | 2014 | SIGMOD | 0.0001194108 |
| 1,935 | A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy | 2014 | VLDB | 0.00010032967 |
| 2,434 | Optimizing error of high-dimensional statistical queries under differential privacy | 2018 | VLDB | 8.8278955e-05 |
| 2,465 | Principled Evaluation of Differentially Private Algorithms using DPBench | 2016 | SIGMOD | 8.7518123e-05 |
| 4,502 | ϵktelo: A Framework for Defining Differentially-Private Computations | 2018 | SIGMOD | 6.1366984e-05 |
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