TuskFlow: An Efficient Graph Database for Long-Running Transactions
Summary: TuskFlow (Neo4j-based) handles long-running "mammoth" graph transactions with a deterministic epoch protocol that reorders regular work and enables parallel mammoth execution. Graph-aware tagging and partitioning reduce conflicts, preserve transactional semantics, avoid blocking writes, and cut tail latency up to 45x. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Georgios Theodorakis (NVIDIA)
- 2. Hugo Firth (Neo4j)
- 3. James Clarkson (Neo4j)
- 4. Natacha Crooks (University of California Berkeley)
- 5. Jim Webber (Neo4j)
BibTeX Citation
@article{theodorakis_vldb25,
title = {{TuskFlow: An Efficient Graph Database for Long-Running Transactions}},
author = {Theodorakis, Georgios and Firth, Hugo and Clarkson, James and Crooks, Natacha and Webber, Jim},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {12},
pages = {4777--4790},
doi = {10.14778/3750601.3750603},
url = {https://doi.org/10.14778/3750601.3750603},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,823 | X-Wim: Massive Parallelization of Weighted Matching in Bipartite Graphs | 2026 | VLDB | 4.9769913e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 29 of 29 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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