DB4ML – An In-Memory Database Kernel with Machine Learning Support
Summary: DB4ML is an in-memory DB kernel enabling in-DBMS execution of user-defined ML algorithms via iterative transactions, avoiding data copies for regulatory compliance. It delivers near specialized ML engine efficiency while remaining extensible, unlike external tools that export data and hard-code algorithms. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Matthias Jasny (Technical University of Darmstadt)
- 2. Tobias Ziegler (Technical University of Darmstadt)
- 3. Tim Kraska (Massachusetts Institute of Technology)
- 4. Uwe Roehm (University of Sydney)
- 5. Carsten Binnig (Technical University of Darmstadt)
BibTeX Citation
@inproceedings{jasny_sigmod20,
title = {{DB4ML – An In-Memory Database Kernel with Machine Learning Support}},
author = {Jasny, Matthias and Ziegler, Tobias and Kraska, Tim and Roehm, Uwe and Binnig, Carsten},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3380575},
url = {https://dl.acm.org/doi/10.1145/3318464.3380575},
year = {2020}
}
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