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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)

Paper ID
h27219d84b59262a9
Venue
VLDB
Year
2023
Pagerank
5.2074327e-05
Overall Rank
9,143 | 38.72%
DOI
10.14778/3611479.3611526
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

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 6 of 6 citing papers.

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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.

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0023948467
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061463175
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046249672
74 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00037164008
142 Neo: A Learned Query Optimizer 2019 VLDB 0.00029114937
174 Optimizing Queries across Diverse Data Sources 1997 VLDB 0.00026736308
188 Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases 1991 VLDB 0.00025858501
224 Self-Driving Database Management Systems 2017 CIDR 0.00023973185
232 TiDB: A Raft-based HTAP Database 2020 VLDB 0.00023776373
309 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.0002143249
320 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021128745
355 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020146245
453 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001801482
458 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017870238
462 Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores 2020 VLDB 0.00017825062
545 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001657599
550 SageDB: A Learned Database System 2019 CIDR 0.00016525249
574 Efficient Transaction Processing in SAP HANA Database – The End of a Column Store Myth 2012 SIGMOD 0.00016142754
676 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014838681
781 Lazy Database Replication with Snapshot Isolation 2006 VLDB 0.00014038257
870 Learning Multi-dimensional Indexes 2020 SIGMOD 0.0001332034
955 Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics 2021 CIDR 0.00012856295
1,157 P-Store: An Elastic Database System with Predictive Provisioning 2018 SIGMOD 0.00011748784
1,190 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011564169
1,238 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00011375179
1,692 Garlic: A New Flavor of Federated Query Processing for DB2 2002 SIGMOD 9.8382183e-05
1,740 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7289523e-05
2,290 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.6813363e-05
2,500 A Demonstration of the BigDAWG Polystore System 2015 VLDB 8.3598881e-05
2,578 Multidatabase Update Issues 1988 SIGMOD 8.2537767e-05
2,619 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 8.1985665e-05
2,772 Instance-Optimized Data Layouts for Cloud Analytics Workloads 2021 SIGMOD 8.0148928e-05
2,852 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.9201312e-05
3,057 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.6865211e-05
3,249 TreeLine: An Update-In-Place Key-Value Store for Modern Storage 2023 VLDB 7.4761584e-05
3,269 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.463682e-05
3,416 RHEEM: Enabling Cross-Platform Data Processing - May The Big Data Be With You! - 2018 VLDB 7.3046808e-05
3,575 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 7.1769215e-05
3,693 The Myria Big Data Management and Analytics System and Cloud Service 2017 CIDR 7.0738965e-05
3,891 Information Translation, Mediation, and Mosaic-Based Browsing in the TSIMMIS System 1995 SIGMOD 6.9252771e-05
4,408 The Distributed Information Search Component (DISCO) and the World Wide Web 1997 SIGMOD 6.6019375e-05
4,798 Cost Models DO Matter: Providing Cost Information for Diverse Data Sources in a Federated System 1999 VLDB 6.3970893e-05
5,112 Towards Scalable Hybrid Stores: Constraint-Based Rewriting to the Rescue 2019 SIGMOD 6.2578491e-05
5,751 The MYRIAD Federated Database Prototype 1994 SIGMOD 5.9903176e-05
6,429 Proteus: Autonomous Adaptive Storage for Mixed Workloads 2022 SIGMOD 5.7691021e-05
6,848 Skeena: Efficient and Consistent Cross-Engine Transactions 2022 SIGMOD 5.6495967e-05
9,731 Database Gyms 2023 CIDR 5.120066e-05
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