TurboFlux: A Fast Continuous Subgraph Matching System for Streaming Graph Data
Summary: TurboFlux enables fast continuous subgraph matching on streaming dynamic graphs via incremental maintenance and a compact intermediate-result representation. Handles edge updates with low overhead, yielding vast throughput gains over prior systems. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Kyongmin Kim (Pohang University of Science and Technology)
- 2. In Seo (Pohang University of Science and Technology)
- 3. Wook-Shin Han (Pohang University of Science and Technology)
- 4. Jeong-Hoon Lee (Pohang University of Science and Technology)
- 5. Sungpack Hong (Oracle)
- 6. Hassan Chafi (Oracle)
- 7. Hyungyu Shin (Pohang University of Science and Technology)
- 8. Geonhwa Jeong (Pohang University of Science and Technology)
BibTeX Citation
@inproceedings{kim_sigmod18,
title = {{TurboFlux: A Fast Continuous Subgraph Matching System for Streaming Graph Data}},
author = {Kim, Kyongmin and Seo, In and Han, Wook-Shin and Lee, Jeong-Hoon and Hong, Sungpack and Chafi, Hassan and Shin, Hyungyu and Jeong, Geonhwa},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3196917},
url = {https://dl.acm.org/doi/10.1145/3183713.3196917},
year = {2018}
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