Virtualizing Cloud Data Infrastructures with BRAD
Summary: BRAD enables declarative, automated cloud data virtualization via VDBEs declaring SQL dialects, perf, and tables. Planner maps VDBEs to engines by workload and budget, enabling colocation, dialect compatibility, and snapshots for multi-engine designs. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Geoffrey X. Yu (Massachusetts Institute of Technology)
- 2. Ziniu Wu (Massachusetts Institute of Technology)
- 3. Amadou Latyr Ngom (Massachusetts Institute of Technology)
- 4. Ferdi Kossmann (Massachusetts Institute of Technology)
- 5. Sophie Zhang (Massachusetts Institute of Technology)
- 6. Tianyu Li (Massachusetts Institute of Technology)
- 7. Tim Kraska (Amazon; Massachusetts Institute of Technology)
- 8. Markos Markakis (Massachusetts Institute of Technology)
- 9. Samuel Madden (Massachusetts Institute of Technology)
BibTeX Citation
@inproceedings{yu_sigmod25,
title = {{Virtualizing Cloud Data Infrastructures with BRAD}},
author = {Yu, Geoffrey X. and Wu, Ziniu and Ngom, Amadou Latyr and Kossmann, Ferdi and Zhang, Sophie and Li, Tianyu and Kraska, Tim and Markakis, Markos and Madden, Samuel},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725141},
url = {https://dl.acm.org/doi/10.1145/3722212.3725141},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 18 | How Good Are Query Optimizers, Really? | 2016 | VLDB | 0.00059284255 |
| 7,755 | Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD | 2024 | VLDB | 5.5519655e-05 |
| 10,066 | Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes | 2023 | VLDB | 5.1643809e-05 |
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