Data Platform for Machine Learning
Summary: MLdp is a purpose-built data management platform for ML datasets, with a minimalist data model, versioning, and data provenance for reproducible experiments. Distinct from MLaaS, it integrates with major ML frameworks and adds privacy/audit controls. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pulkit Agrawal (Apple)
- 2. Rajat Arya (Apple)
- 3. Aanchal Bindal (Apple)
- 4. Sandeep Bhatia (Apple)
- 5. Anupriya Gagneja (Apple)
- 6. Joseph Godlewski (Apple)
- 7. Yucheng Low (Apple)
- 8. Timothy Muss (Apple)
- 9. Mudit Manu Paliwal (Apple)
- 10. Sethu Raman (Apple)
- 11. Vishrut Shah (Apple)
- 12. Bochao Shen (Apple)
- 13. Laura Sugden (Apple)
- 14. Kaiyu Zhao (Apple)
- 15. Ming-Chuan Wu (Apple)
BibTeX Citation
@inproceedings{agrawal_sigmod19,
title = {{Data Platform for Machine Learning}},
author = {Agrawal, Pulkit and Arya, Rajat and Bindal, Aanchal and Bhatia, Sandeep and Gagneja, Anupriya and Godlewski, Joseph and Low, Yucheng and Muss, Timothy and Paliwal, Mudit Manu and Raman, Sethu and Shah, Vishrut and Shen, Bochao and Sugden, Laura and Zhao, Kaiyu and Wu, Ming-Chuan},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3314050},
url = {https://dl.acm.org/doi/10.1145/3299869.3314050},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,947 | Overton: A Data System for Monitoring and Improving Machine-Learned Products | 2020 | CIDR | 7.0040437e-05 |
| 4,621 | spade: Synthesizing Data Quality Assertions for Large Language Model Pipelines | 2024 | VLDB | 6.6024412e-05 |
| 8,050 | Capturing and Querying Fine-grained Provenance of Preprocessing Pipelines in Data Science | 2021 | VLDB | 5.5000099e-05 |
| 9,245 | Towards Observability for Production Machine Learning Pipelines | 2022 | VLDB | 5.2992628e-05 |
| 11,355 | Git is for Data | 2023 | CIDR | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 415 | SystemML: Declarative Machine Learning on Spark | 2016 | VLDB | 0.0001888524 |
| 514 | Goods: Organizing Google's Datasets | 2016 | SIGMOD | 0.00017178673 |
| 532 | MLbase: A Distributed Machine-learning System | 2013 | CIDR | 0.00017072641 |
| 1,077 | DataHub: Collaborative Data Science & Dataset Version Management at Scale | 2015 | CIDR | 0.00012269438 |
| 2,235 | Decibel: The Relational Dataset Branching System | 2016 | VLDB | 8.8913373e-05 |
| 5,026 | ORPHEUSDB: A Lightweight Approach to Relational Dataset Versioning | 2017 | SIGMOD | 6.3970621e-05 |
| 8,233 | Crossing the finish line faster when paddling the Data Lake with KAYAK | 2017 | VLDB | 5.4610752e-05 |
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|---|---|---|---|---|
| 1 | 11,516 | Data Management Opportunities for Foundation Models | 2022 | CIDR |
| 2 | 4,067 | Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches | 2021 | VLDB |
| 3 | 9,962 | Structure-Aware Machine Learning over Multi-Relational Databases | 2021 | SIGMOD |
| 4 | 1,756 | SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle | 2020 | CIDR |
| 5 | 7,855 | ItemSuggest: A Data Management Platform for Machine Learned Ranking Services | 2019 | CIDR |
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| 8 | 11,512 | Towards Observability for Machine Learning Pipelines | 2022 | CIDR |
| 9 | 532 | MLbase: A Distributed Machine-learning System | 2013 | CIDR |
| 10 | 1,250 | Data Management in Machine Learning: Challenges, Techniques, and Systems | 2017 | SIGMOD |