SageDB: An Instance-Optimized Data Analytics System
Summary: First instance-optimized data system auto-tunes for a workload by synthesizing indexes, estimators, and analytics components into a cohesive stack. Outperforms a commercial cloud analytics system by 3x on end-to-end workloads and 250x on queries. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jialin Ding (Massachusetts Institute of Technology)
- 2. Ryan Marcus (University of Pennsylvania)
- 3. Andreas Kipf (Massachusetts Institute of Technology)
- 4. Vikram Nathan (Massachusetts Institute of Technology)
- 5. Aniruddha Nrusimha (Massachusetts Institute of Technology)
- 6. Kapil Vaidya (Massachusetts Institute of Technology)
- 7. Alexander van Renen (Friedrich-Alexander-Universität Erlangen-Nürnberg)
- 8. Tim Kraska (Massachusetts Institute of Technology)
BibTeX Citation
@article{ding_vldb22,
title = {{SageDB: An Instance-Optimized Data Analytics System}},
author = {Ding, Jialin and Marcus, Ryan and Kipf, Andreas and Nathan, Vikram and Nrusimha, Aniruddha and Vaidya, Kapil and van Renen, Alexander and Kraska, Tim},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {13},
pages = {4062--4078},
doi = {10.14778/3565838.3565857},
url = {https://doi.org/10.14778/3565838.3565857},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,408 | Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet | 2024 | VLDB | 8.6154404e-05 |
| 7,465 | Automated Multidimensional Data Layouts in Amazon Redshift | 2024 | SIGMOD | 5.6108826e-05 |
| 7,660 | Pruning in Snowflake: Working Smarter, Not Harder | 2025 | SIGMOD | 5.5736132e-05 |
| 8,042 | Grep: A Graph Learning Based Database Partitioning System | 2023 | SIGMOD | 5.5015896e-05 |
| 8,591 | A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach | 2025 | SIGMOD | 5.4059856e-05 |
| 8,849 | ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation | 2024 | SIGMOD | 5.3577504e-05 |
| 10,505 | The Case For Language Model Approximated LIKE Predicate | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 30 of 30 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 4 | 4,053 | Database-Agnostic Workload Management | 2019 | CIDR |
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| 6 | 518 | Towards a Unified Architecture for in-RDBMS Analytics | 2012 | SIGMOD |
| 7 | 5,329 | SeeDB: Visualizing Database Queries Efficiently | 2014 | VLDB |
| 8 | 5,978 | From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems | 2019 | SIGMOD |
| 9 | 5,974 | Towards instance-optimized data systems | 2021 | VLDB |
| 10 | 568 | SageDB: A Learned Database System | 2019 | CIDR |