BRRL: A Recovery Library for Main-Memory Applications in the Cloud
Summary: BRRL is a fault-tolerance library for distributed in-memory cloud apps at frequent consistency points. It uses a simple table abstraction and schema-aware checkpointing to cut overhead via data-parallelism, avoiding complex concurrency control; demonstrated on a distributed TP system and scientific simulations. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Tuan Cao (Cornell University)
- 2. Benjamin Sowell (Cornell University)
- 3. Marcos Vaz Salles (Cornell University)
- 4. Alan Demers (Cornell University)
- 5. Johannes Gehrke (Cornell University)
BibTeX Citation
@inproceedings{cao_sigmod11,
title = {{BRRL: A Recovery Library for Main-Memory Applications in the Cloud}},
author = {Cao, Tuan and Sowell, Benjamin and Salles, Marcos Vaz and Demers, Alan and Gehrke, Johannes},
series = {{SIGMOD} '11},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1989323.1989462},
url = {https://dl.acm.org/doi/10.1145/1989323.1989462},
year = {2011}
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 68 | The End of an Architectural Era (It’s Time for a Complete Rewrite) | 2007 | VLDB | 0.00038446206 |
| 1,255 | Fast Checkpoint Recovery Algorithms for Frequently Consistent Applications | 2011 | SIGMOD | 0.00011472627 |
| 4,047 | Behavioral Simulations in MapReduce | 2010 | VLDB | 6.9380465e-05 |
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