Modyn: Data-Centric Machine Learning Pipeline Orchestration

Summary: Modyn is a data-centric ML platform for growing datasets, declaratively configuring training with data-selection and triggering policies. Composite models for fair evaluation; open benchmarks; high-throughput, sample-level data selection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 7112
Venue: SIGMOD
Year: 2025
Pagerank: 5.3462965e-05
Overall Rank: 8,949 | 38.61%
DOI: 10.1145/3709705

Incoming Non-self Citations Over Time

Authors

1. Maximilian Böther (ETH Zurich)
2. Ties Robroek (IT University of Copenhagen)
3. Viktor Gsteiger (ETH Zurich)
4. Robin Holzinger (Technical University of Munich)
5. Xianzhe Ma (ETH Zurich)
6. Pınar Tözün (IT University of Copenhagen)
7. Ana Klimovic (ETH Zurich)

BibTeX Citation

@inproceedings{bother_sigmod25,
        title = {{Modyn: Data-Centric Machine Learning Pipeline Orchestration}},
        author = {Böther, Maximilian and Robroek, Ties and Gsteiger, Viktor and Holzinger, Robin and Ma, Xianzhe and Tözün, Pınar and Klimovic, Ana},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3709705},
        url = {https://dl.acm.org/doi/10.1145/3709705},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,272	NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis]	2026	SIGMOD	5.093636e-05
10,540	CAPS: Cost-Aware ML Pipeline Selection	2026	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
34	The Design Of Postgres	1986	SIGMOD	0.00049302774
1,350	Automating Large-Scale Data Quality Verification	2018	VLDB	0.00011065626
2,018	tf.data: A Machine Learning Data Processing Framework	2021	VLDB	9.3001937e-05
2,657	Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities	2021	SIGMOD	8.2887895e-05
2,688	Accelerating Recommendation System Training by Leveraging Popular Choices	2022	VLDB	8.2564305e-05
3,670	Learning to Validate the Predictions of Black Box Classifiers on Unseen Data	2020	SIGMOD	7.2118928e-05
4,130	PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models	2020	SIGMOD	6.8839621e-05
7,106	Incremental Tabular Learning on Heterogeneous Feature Space	2023	SIGMOD	5.7005795e-05
7,395	Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines	2023	SIGMOD	5.6257796e-05
8,050	Capturing and Querying Fine-grained Provenance of Preprocessing Pipelines in Data Science	2021	VLDB	5.5000099e-05
8,134	DORIAN in action: Assisted Design of Data Science Pipelines	2022	VLDB	5.4811783e-05
9,245	Towards Observability for Production Machine Learning Pipelines	2022	VLDB	5.2992628e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	2,018	tf.data: A Machine Learning Data Processing Framework	2021	VLDB
2	9,245	Towards Observability for Production Machine Learning Pipelines	2022	VLDB
3	6,309	Materialization and Reuse Optimizations for Production Data Science Pipelines	2022	SIGMOD
4	10,999	cedar: Optimized and Unified Machine Learning Input Data Pipelines	2025	VLDB
5	1,756	SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle	2020	CIDR
6	7,395	Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines	2023	SIGMOD
7	11,512	Towards Observability for Machine Learning Pipelines	2022	CIDR
8	2,657	Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities	2021	SIGMOD
9	4,592	Data Platform for Machine Learning	2019	SIGMOD
10	7,473	The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development	2020	SIGMOD