Rheem: Enabling Multi-Platform Task Execution
Summary: Rheem enables multi-platform task execution across heterogeneous data systems via a three-layer data processing abstraction. It introduces a novel cross-platform query optimization approach and validates on ML, data cleaning, and data fusion workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Divy Agrawal (University of California Santa Barbara)
- 2. Lamine Ba (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 3. Laure Berti-Equille (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 4. Sanjay Chawla (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 5. Ahmed Elmagarmid (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 6. Hossam Hammady (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 7. Yasser Idris (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 8. Zoi Kaoudi (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 9. Zuhair Khayyat (King Abdullah University of Science and Technology)
- 10. Sebastian Kruse (Hasso Plattner Institute)
- 11. Mourad Ouzzani (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 12. Paolo Papotti (Arizona State University)
- 13. Jorge-Arnulfo Quiané-Ruiz (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 14. Nan Tang (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 15. Mohammed J. Zaki (Rensselaer Polytechnic Institute)
BibTeX Citation
@inproceedings{agrawal_sigmod16,
title = {{Rheem: Enabling Multi-Platform Task Execution}},
author = {Agrawal, Divy and Ba, Lamine and Berti-Equille, Laure and Chawla, Sanjay and Elmagarmid, Ahmed and Hammady, Hossam and Idris, Yasser and Kaoudi, Zoi and Khayyat, Zuhair and Kruse, Sebastian and Ouzzani, Mourad and Papotti, Paolo and Quiané-Ruiz, Jorge-Arnulfo and Tang, Nan and Zaki, Mohammed J.},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2889414},
url = {https://dl.acm.org/doi/10.1145/2882903.2889414},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,908 | AI Meets Database: AI4DB and DB4AI | 2021 | SIGMOD | 7.8742664e-05 |
| 3,402 | RHEEM: Enabling Cross-Platform Data Processing - May The Big Data Be With You! - | 2018 | VLDB | 7.3304477e-05 |
| 5,700 | A Demo of the Data Civilizer System | 2017 | SIGMOD | 6.0317753e-05 |
| 6,141 | Expand your Training Limits! Generating Training Data for ML-based Data Management | 2021 | SIGMOD | 5.8733296e-05 |
| 7,142 | A Cost-based Optimizer for Gradient Descent Optimization | 2017 | SIGMOD | 5.600563e-05 |
| 9,034 | The Power of Nested Parallelism in Big Data Processing – Hitting Three Flies with One Slap – | 2021 | SIGMOD | 5.2334993e-05 |
| 9,922 | Unified Data Analytics: State-of-the-art and Open Problems | 2022 | VLDB | 5.1103839e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 697 | NADEEF: A Commodity Data Cleaning System | 2013 | SIGMOD | 0.00014694048 |
| 2,423 | BigDansing: A System for Big Data Cleansing | 2015 | SIGMOD | 8.4877894e-05 |
| 2,492 | A Demonstration of the BigDAWG Polystore System | 2015 | VLDB | 8.3899912e-05 |
| 3,295 | Lightning Fast and Space Efficient Inequality Joins | 2015 | VLDB | 7.448168e-05 |
| 4,650 | Temporal Rules Discovery for Web Data Cleaning | 2016 | VLDB | 6.4858157e-05 |
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