DeQL Studio: Declarative Decision-Making over Relational Data
Summary: DeQL extends SQL with declarative optimization over relational data, letting its Planner infer efficient mathematical formulations rather than forcing users to choose them. DeQL Studio demonstrates adaptive formulation switching and solver warm starts, achieving 30× speedups via automatic MCF detection. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Matteo Brucato (OSM Data)
- 2. Fjodor Kholodkov (OSM Data)
- 3. Soren Little (OSM Data)
- 4. Jakob Mayer (OSM Data)
- 5. Duc Nguyen (OSM Data)
BibTeX Citation
@article{brucato_vldb26,
title = {{DeQL Studio: Declarative Decision-Making over Relational Data}},
author = {Brucato, Matteo and Kholodkov, Fjodor and Little, Soren and Mayer, Jakob and Nguyen, Duc},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4614--4617},
doi = {10.14778/3827998.3828079},
url = {https://doi.org/10.14778/3827998.3828079},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,822 | Decisionhouse: Prescriptive Analytics in the Data Stack | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,172 | sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization | 2020 | VLDB | 5.0682654e-05 |
| 10,822 | Decisionhouse: Prescriptive Analytics in the Data Stack | 2026 | VLDB | 4.9793485e-05 |
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