Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype?
Summary: Examines ML–DB frontier, outlining concrete opportunities for data management, learned query processing, and ML integration, and assesses substance versus hype. Discusses pitfalls, hype risks, and guidance for database researchers pursuing ML. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Christopher Ré
- 2. Divy Agrawal
- 3. Magdalena Balazinska
- 4. Michael Cafarella
- 5. Michael Jordan
- 6. Tim Kraska
- 7. Raghu Ramakrishnan
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 832 | Learning Linear Regression Models over Factorized Joins | 2016 | SIGMOD | 0.00016089705 |
| 2,660 | Vertica-ML: Distributed Machine Learning in Vertica Database | 2020 | SIGMOD | 8.3614044e-05 |
| 2,939 | AIDA - Abstraction for Advanced In-Database Analytics | 2018 | VLDB | 7.8514162e-05 |
| 3,466 | AI Meets Database: AI4DB and DB4AI | 2021 | SIGMOD | 7.0645718e-05 |
| 4,745 | Rafiki: Machine Learning as an Analytics Service System | 2019 | VLDB | 5.9466323e-05 |
| 5,787 | Machine Learning for Databases | 2021 | VLDB | 5.3256401e-05 |
| 8,365 | NeurDB: On the Design and Implementation of an AI-powered Autonomous Database | 2025 | CIDR | 4.5305127e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,466 | AI Meets Database: AI4DB and DB4AI | 2021 | SIGMOD | 7.0645718e-05 |
| 1,534 | Data Management in Machine Learning: Challenges, Techniques, and Systems | 2017 | SIGMOD | 0.00011462072 |
| 5,250 | One Model to Rule them All: Towards Zero-Shot Learning for Databases | 2022 | CIDR | 5.6007779e-05 |
| 8,847 | Towards Foundation Database Models | 2025 | CIDR | 4.4329366e-05 |
| 13,526 | Database Systems Research on Data Mining | 2010 | SIGMOD | - |
| 6,774 | A Unified Transferable Model for ML-Enhanced DBMS | 2022 | CIDR | 4.9253635e-05 |
| 4,913 | Machine Learning for Big Data | 2013 | SIGMOD | 5.8320287e-05 |
| 10,847 | Machine Learning for Graph Data Management and Query Processing | 2025 | VLDB | 4.1905499e-05 |
| 3,866 | Cloudy with High Chance of DBMS: A 10-year Prediction for Enterprise-Grade ML | 2020 | CIDR | 6.6795497e-05 |
| 5,787 | Machine Learning for Databases | 2021 | VLDB | 5.3256401e-05 |