Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes
Summary: BRAD auto-builds an instance‑optimized data mesh exposing a unified relational view over heterogeneous engines, hiding engine selection and data motion from users. ML (offline + online probing) learns engine cost models to route queries, automate tuning/scaling/migration, and recommend system changes. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tim Kraska (Amazon; Massachusetts Institute of Technology)
- 2. Tianyu Li (Massachusetts Institute of Technology)
- 3. Samuel Madden (Massachusetts Institute of Technology)
- 4. Markos Markakis (Massachusetts Institute of Technology)
- 5. Amadou Ngom (Massachusetts Institute of Technology)
- 6. Ziniu Wu (Massachusetts Institute of Technology)
- 7. Geoffrey X. Yu (Massachusetts Institute of Technology)
BibTeX Citation
@article{kraska_vldb23,
title = {{Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes}},
author = {Kraska, Tim and Li, Tianyu and Madden, Samuel and Markakis, Markos and Ngom, Amadou and Wu, Ziniu and Yu, Geoffrey X.},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {11},
pages = {3293--3301},
doi = {10.14778/3611479.3611526},
url = {https://doi.org/10.14778/3611479.3611526},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,755 | Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD | 2024 | VLDB | 5.5519655e-05 |
| 8,375 | Serverless State Management Systems | 2024 | CIDR | 5.4391978e-05 |
| 10,742 | Virtualizing Cloud Data Infrastructures with BRAD | 2025 | SIGMOD | 5.093636e-05 |
| 10,761 | Fast and Scalable Data Transfer Across Data Systems | 2025 | SIGMOD | 5.093636e-05 |
| 10,969 | Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 47 of 47 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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