PilotScope: Steering Databases with Machine Learning Drivers
Summary: PilotScope is middleware for deploying AI4DB algorithms, separating ML-centric AI4DB drivers from engine-specific database interactors. This abstraction lowers integration cost and enables portable, cross-database benchmarking of tuning and optimization techniques. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Rong Zhu (Alibaba)
- 2. Lianggui Weng (Alibaba)
- 3. Wenqing Wei (Alibaba; University of Science and Technology Beijing)
- 4. Di Wu (Alibaba; Huazhong University of Science and Technology)
- 5. Jiazhen Peng (Alibaba; Zhejiang University)
- 6. Yifan Wang (Alibaba; University of Florida)
- 7. Bolin Ding (Alibaba)
- 8. Defu Lian (University of Science and Technology Beijing)
- 9. Bolong Zheng (Huazhong University of Science and Technology)
- 10. Jingren Zhou (Alibaba)
BibTeX Citation
@article{zhu_vldb24,
title = {{PilotScope: Steering Databases with Machine Learning Drivers}},
author = {Zhu, Rong and Weng, Lianggui and Wei, Wenqing and Wu, Di and Peng, Jiazhen and Wang, Yifan and Ding, Bolin and Lian, Defu and Zheng, Bolong and Zhou, Jingren},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {5},
pages = {980--993},
doi = {10.14778/3641204.3641209},
url = {https://doi.org/10.14778/3641204.3641209},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,163 | Learned Offline Query Planning via Bayesian Optimization | 2025 | SIGMOD | 5.4751517e-05 |
| 8,221 | NeurDB: On the Design and Implementation of an AI-powered Autonomous Database | 2025 | CIDR | 5.4640314e-05 |
| 9,601 | Low Rank Learning for Offline Query Optimization | 2025 | SIGMOD | 5.2487799e-05 |
| 10,028 | PRICE: A Pretrained Model for Cross-Database Cardinality Estimation | 2025 | VLDB | 5.1745962e-05 |
| 10,316 | GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints | 2026 | SIGMOD | 5.093636e-05 |
| 10,559 | OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning | 2026 | VLDB | 5.093636e-05 |
| 10,660 | Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions | 2025 | SIGMOD | 5.093636e-05 |
| 10,829 | FB+-tree: A Memory-Optimized B+-tree with Latch-Free Update | 2025 | VLDB | 5.093636e-05 |
| 11,298 | Native Distributed Databases: Problems, Challenges and Opportunities | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 51 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,123 | BASE: Bridging the Gap between Cost and Latency for Query Optimization | 2023 | VLDB | 5.3193264e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 9,962 | Structure-Aware Machine Learning over Multi-Relational Databases | 2021 | SIGMOD |
| 2 | 3,586 | Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation | 2021 | VLDB |
| 3 | 4,468 | One Model to Rule them All: Towards Zero-Shot Learning for Databases | 2022 | CIDR |
| 4 | 7,785 | Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems | 2022 | SIGMOD |
| 5 | 7,066 | Aero: Adaptive Query Processing of ML Queries | 2025 | SIGMOD |
| 6 | 6,357 | A Unified Transferable Model for ML-Enhanced DBMS | 2022 | CIDR |
| 7 | 5,059 | Steering Query Optimizers: A Practical Take on Big Data Workloads | 2021 | SIGMOD |
| 8 | 3,961 | MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems | 2021 | SIGMOD |
| 9 | 2,786 | DB4ML – An In-Memory Database Kernel with Machine Learning Support | 2020 | SIGMOD |
| 10 | 2,888 | AI Meets Database: AI4DB and DB4AI | 2021 | SIGMOD |