Machine Learning, Linear Algebra, and More: Is SQL All You Need?
Summary: Systematic translation of procedural algorithms (machine learning, linear algebra, and other intensive computations) into pure SQL, enabling complex in-DB declarative implementations. Shows modern engines (e.g., HyPer) can match or outperform native linear-algebra libraries. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mark Blacher
- 2. Joachim Giesen
- 3. Sören Laue
- 4. Julien Klaus
- 5. Viktor Leis
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,548 | Efficient and Portable Einstein Summation in SQL | 2023 | SIGMOD | 6.089487e-05 |
| 5,311 | A Critique of Modern SQL And A Proposal Towards A Simple and Expressive Query Language | 2024 | CIDR | 5.5712968e-05 |
| 6,157 | Optimizing Tensor Programs on Flexible Storage | 2023 | SIGMOD | 5.1755682e-05 |
| 6,703 | YeSQL: “You extend SQL” with Rich and Highly Performant User-Defined Functions in Relational Databases | 2022 | VLDB | 4.9514593e-05 |
| 8,580 | Efficient Execution of User-Defined Functions in SQL Queries | 2023 | VLDB | 4.4876382e-05 |
| 9,813 | Optimizing Nested Recursive Queries | 2024 | SIGMOD | 4.2742278e-05 |
| 9,883 | SQL Engines Excel at the Execution of Imperative Programs | 2024 | VLDB | 4.2594931e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 169 | MAD Skills: New Analysis Practices for Big Data | 2009 | VLDB | 0.00038967371 |
| 1,107 | Froid: Optimization of Imperative Programs in a Relational Database | 2018 | VLDB | 0.0001397627 |
| 3,649 | One WITH RECURSIVE is Worth Many GOTOs | 2021 | SIGMOD | 6.8764882e-05 |
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