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Adore: Differentially Oblivious Relational Database Operators

Summary: Adore develops differentially-oblivious relational operators (selection+projection, grouping+aggregation, foreign-key join) and formally proves they meet differential obliviousness, trading bounded leakage for lower access-pattern cost. Compared to fully-oblivious baselines, Adore cuts cache/runtime complexity and output size, yielding up to 7.4× speedup. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
hb01110b78b4217df
Venue
VLDB
Year
2023
Pagerank
6.908248e-05
Overall Rank
3,915 | 73.76%
DOI
10.14778/3574245.3574267
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{qin_vldb23,
        title = {{Adore: Differentially Oblivious Relational Database Operators}},
        author = {Qin, Lianke and Jayaram, Rajesh and Shi, Elaine and Song, Zhao and Zhuo, Danyang and Chu, Shumo},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {4},
        pages = {842--855},
        doi = {10.14778/3574245.3574267},
        url = {https://doi.org/10.14778/3574245.3574267},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
23 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00055523999
52 The Snowflake Elastic Data Warehouse 2016 SIGMOD 0.00041439488
63 Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases 2017 SIGMOD 0.00038609177
64 Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis 2009 SIGMOD 0.00038378358
226 Amazon Redshift and the Case for Simpler Data Warehouses 2015 SIGMOD 0.0002389883
279 Towards Practical Differential Privacy for SQL Queries 2018 VLDB 0.00022277389
539 TrustedDB: A Trusted Hardware based Database with Privacy and Data Confidentiality 2011 SIGMOD 0.00016701521
1,134 Dremel: A Decade of Interactive SQL Analysis at Web Scale 2020 VLDB 0.00011863043
1,170 PrivateSQL: A Differentially Private SQL Query Engine 2019 VLDB 0.00011687052
1,422 Azure SQL Database Always Encrypted 2020 SIGMOD 0.00010698141
1,499 SMCQL: Secure Querying for Federated Databases 2017 VLDB 0.00010445281
1,651 Arx: An Encrypted Database using Semantically Secure Encryption 2019 VLDB 9.9665279e-05
1,966 GUPT: Privacy Preserving Data Analysis Made Easy 2012 SIGMOD 9.282558e-05
2,032 Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations 2019 VLDB 9.1412376e-05
2,583 Secure Database-as-a-Service with Cipherbase 2013 SIGMOD 8.2435615e-05
4,212 VeriDB: An SGX-based Verifiable Database 2021 SIGMOD 6.7201474e-05
4,390 A Framework for Adversarially Robust Streaming Algorithms 2020 PODS 6.6110397e-05
4,738 Practical Private Range Search Revisited 2016 SIGMOD 6.4295783e-05
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