Data Management in Machine Learning: Challenges, Techniques, and Systems
Summary: Survey of data-management challenges and systems for ML workloads. Three lines of work: integrating ML with DBMS; adapting DB techniques to ML (queries, partitioning, compression); and combining data-management with ML lifecycles, plus open directions. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Arun Kumar
- 2. Matthias Boehm
- 3. Jun Yang
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 63 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,834 | Is Data Management the Beating Heart of AI Systems? | 2022 | SIGMOD | 4.2706095e-05 |
| 4,006 | Data Platform for Machine Learning | 2019 | SIGMOD | 6.5371762e-05 |
| 936 | Data Lake Management: Challenges and Opportunities | 2019 | VLDB | 0.00015197838 |
| 7,652 | Machine Learning for Cloud Data Systems: the Progress so far and the Path Forward | 2021 | VLDB | 4.6831938e-05 |
| 7,016 | LLM for Data Management | 2024 | VLDB | 4.8561622e-05 |
| 8,340 | Deep Learning: Systems and Responsibility | 2021 | SIGMOD | 4.5381546e-05 |
| 10,847 | Machine Learning for Graph Data Management and Query Processing | 2025 | VLDB | 4.1905499e-05 |
| 8,637 | Machine Learning for Data Management: Problems and Solutions | 2018 | SIGMOD | 4.4755972e-05 |
| 1,422 | Data Management Challenges in Production Machine Learning | 2017 | SIGMOD | 0.00012050431 |
| 4,913 | Machine Learning for Big Data | 2013 | SIGMOD | 5.8320287e-05 |