Back to papers
Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems
Summary: TScout collects training data for self-driving DBMSs by annotating source with hooks and generating kernel-level BPF probes. It aggregates workload, config, internal state, and hardware metrics in a PostgreSQL-compatible DBMS, with ~7% overhead, yielding better ML behavior models for OLTP/OLAP.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6298
- Venue
- SIGMOD
- Year
- 2022
- Pagerank
- 4.5965825e-05
- Overall Rank
- 8,036 | 44.15%
- DOI
-
10.1145/3514221.3517845
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 6,883 |
PilotScope: Steering Databases with Machine Learning Drivers |
2024 |
VLDB |
4.8918682e-05 |
| 8,003 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
4.6049527e-05 |
| 8,011 |
CAMAL: Optimizing LSM-trees via Active Learning |
2024 |
SIGMOD |
4.6022693e-05 |
| 8,668 |
Algorithmic Complexity Attacks on Dynamic Learned Indexes |
2024 |
VLDB |
4.4671214e-05 |
| 8,838 |
BPF-DB: A Kernel-Embedded Transactional Database Management System For eBPF Applications |
2025 |
SIGMOD |
4.4346105e-05 |
| 9,012 |
Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems |
2024 |
VLDB |
4.4059413e-05 |
| 9,189 |
Practical DB-OS Co-Design with Privileged Kernel Bypass |
2025 |
SIGMOD |
4.3750062e-05 |
| 9,469 |
Database Gyms |
2023 |
CIDR |
4.3304872e-05 |
| 9,787 |
The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format |
2024 |
SIGMOD |
4.2799988e-05 |
| 9,955 |
SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression |
2025 |
VLDB |
4.2332427e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 59 |
Efficiently Compiling Efficient Query Plans for Modern Hardware |
2011 |
VLDB |
0.0006445664 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036859633 |
| 339 |
OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases |
2014 |
VLDB |
0.00026895683 |
| 348 |
Serializable Isolation for Snapshot Databases |
2008 |
SIGMOD |
0.00026473778 |
| 371 |
Self-Driving Database Management Systems |
2017 |
CIDR |
0.00025382677 |
| 419 |
Fast Serializable Multi-Version Concurrency Control for Main-Memory Database Systems |
2015 |
SIGMOD |
0.00023720294 |
| 423 |
Tuning Database Configuration Parameters with iTuned |
2009 |
VLDB |
0.00023628474 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 704 |
Query-based Workload Forecasting for Self-Driving Database Management Systems |
2018 |
SIGMOD |
0.00017785557 |
| 779 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016719473 |
| 796 |
SageDB: A Learned Database System |
2019 |
CIDR |
0.00016541749 |
| 876 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.00015660534 |
| 2,050 |
Automatically Indexing Millions of Databases in Microsoft Azure SQL Database |
2019 |
SIGMOD |
9.6883066e-05 |
| 2,239 |
Performance and Resource Modeling in Highly-Concurrent OLTP Workloads |
2013 |
SIGMOD |
9.2163469e-05 |
| 3,580 |
Query Performance Prediction for Concurrent Queries using Graph Embedding |
2020 |
VLDB |
6.9460425e-05 |
| 3,725 |
Estimating Cardinalities with Deep Sketches |
2019 |
SIGMOD |
6.8117015e-05 |
| 4,151 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
6.4020605e-05 |
| 4,587 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.0594195e-05 |
| 6,668 |
Mainlining Databases: Supporting Fast Transactional Workloads on Universal Columnar Data File Formats |
2021 |
VLDB |
4.9647176e-05 |
| 8,180 |
Demonstrating UDO: A Unified Approach for Optimizing Transaction Code, Physical Design, and System Parameters via Reinforcement Learning |
2021 |
SIGMOD |
4.5627116e-05 |
Semantically Similar Papers