Fast and Scalable Data Transfer Across Data Systems
Summary: XDBC decomposes data transfer into modular components with pluggable implementations for heterogeneous systems. Automatic optimization of transfer configurations per workload yields up to 5x speedups vs generic tools, rivaling specialized approaches. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Haralampos Gavriilidis (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 2. Kaustubh Beedkar (Indian Institute of Technology Delhi)
- 3. Matthias Boehm (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 4. Volker Markl (Berlin Institute for the Foundations of Learning and Data; German National Research Center for Information Technology; Technical University of Berlin)
BibTeX Citation
@inproceedings{gavriilidis_sigmod25,
title = {{Fast and Scalable Data Transfer Across Data Systems}},
author = {Gavriilidis, Haralampos and Beedkar, Kaustubh and Boehm, Matthias and Markl, Volker},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725294},
url = {https://dl.acm.org/doi/10.1145/3725294},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,773 | Incremental Stream Query Deployment under Continuous Infrastructure Changes in the Cloud-Edge Continuum | 2026 | VLDB | 4.9793485e-05 |
| 10,932 | IMLane: Composable Framework for Efficient AI Function Execution in Database Engine | 2026 | VLDB | 4.9793485e-05 |
| 11,397 | Enter the Warp: Fast and Adaptive Data Transfer with XDBC | 2025 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 38 of 38 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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