Perseus: Achieving Strong Consistency and High Data Freshness for Scalable Geo-distributed HTAP
Summary: Perseus enforces strong consistency for transactions and analytical queries in scalable geo-distributed HTAP by augmenting dependency graphs with data versions and full inter-version dependencies. A dynamic snapshot algorithm selectively includes updates to minimize analytical staleness, achieving up to ~90% lower visibility delay while remaining scalable and robust to network instability. (summarized by gpt-5-mini on Feb 11 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Haoze Song (University of Hong Kong)
- 2. Xusheng Chen (Huawei)
- 3. Ruijie Gong (University of Hong Kong)
- 4. Zekai Sun (University of Hong Kong)
- 5. Tianxiang Shen (University of Hong Kong)
- 6. Cheng Li (University of Science and Technology Beijing)
- 7. Hao Feng (Huawei)
- 8. Sen Wang (Huawei)
- 9. Heming Cui (University of Hong Kong)
BibTeX Citation
@inproceedings{song_sigmod26,
title = {{Perseus: Achieving Strong Consistency and High Data Freshness for Scalable Geo-distributed HTAP}},
author = {Song, Haoze and Chen, Xusheng and Gong, Ruijie and Sun, Zekai and Shen, Tianxiang and Li, Cheng and Feng, Hao and Wang, Sen and Cui, Heming},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3749178},
url = {https://dl.acm.org/doi/10.1145/3749178},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 34 of 34 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 11,624 | Native Distributed Databases: Problems, Challenges and Opportunities | 2024 | VLDB |
| 2 | 6,026 | Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads | 2022 | VLDB |
| 3 | 2,451 | The Homeostasis Protocol: Avoiding Transaction Coordination Through Program Analysis | 2015 | SIGMOD |
| 4 | 4,343 | Minimizing Commit Latency of Transactions in Geo-Replicated Data Stores | 2015 | SIGMOD |
| 5 | 7,409 | Galaxybase: A High Performance Native Distributed Graph Database for HTAP | 2024 | VLDB |
| 6 | 10,679 | Performant Synchronization in Geo-Distributed Databases | 2026 | SIGMOD |
| 7 | 5,256 | ByteHTAP: ByteDance’s HTAP System with High Data Freshness and Strong Data Consistency | 2022 | VLDB |
| 8 | 11,024 | Vodka: Rethink Benchmarking Philosophy in HTAP Systems | 2026 | VLDB |
| 9 | 6,944 | GeoGauss: Strongly Consistent and Light-Coordinated OLTP for Geo-Replicated SQL Database | 2023 | SIGMOD |
| 10 | 6,600 | Proteus: Autonomous Adaptive Storage for Mixed Workloads | 2022 | SIGMOD |