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CUTTANA: Scalable Graph Partitioning for Faster Distributed Graph Databases and Analytics
Summary: CUTTANA is a streaming graph partitioner that buffers vertices and uses scalable coarsening/refinement to defer assignments and approximate a global view, reducing edge-cut and communication volume. Parallel CUTTANA matches streaming latency while cutting analytics runtimes up to 59% and improving graph-DB throughput up to 23% versus prior streaming partitioners.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13807
- Venue
- VLDB
- Year
- 2025
- Pagerank
- 4.427232e-05
- Overall Rank
- 8,900 | 38.09%
- DOI
-
10.14778/3696435.3696437
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 4 |
Pregel: A System for Large-Scale Graph Processing |
2010 |
SIGMOD |
0.0019005923 |
| 331 |
The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing |
2018 |
VLDB |
0.00027214222 |
| 536 |
The LDBC Social Network Benchmark: Interactive Workload |
2015 |
SIGMOD |
0.00020722862 |
| 2,494 |
Streaming Graph Partitioning: An Experimental Study |
2018 |
VLDB |
8.6508229e-05 |
| 2,595 |
LEOPARD: Lightweight Edge-Oriented Partitioning and Replication for Dynamic Graphs |
2016 |
VLDB |
8.4735292e-05 |
| 3,287 |
GraphScope: A Unified Engine For Big Graph Processing |
2021 |
VLDB |
7.2739447e-05 |
| 3,573 |
A Scalable Distributed Graph Partitioner |
2015 |
VLDB |
6.954939e-05 |
| 3,839 |
Experimental Analysis of Streaming Algorithms for Graph Partitioning |
2019 |
SIGMOD |
6.7120651e-05 |
| 4,020 |
TopoX: Topology Refactorization for Efficient Graph Partitioning and Processing |
2019 |
VLDB |
6.5237459e-05 |
| 4,234 |
Distributed Edge Partitioning for Trillion-edge Graphs |
2019 |
VLDB |
6.3355073e-05 |
| 4,450 |
A1: A Distributed In-Memory Graph Database |
2020 |
SIGMOD |
6.1741566e-05 |
| 5,231 |
ByteGraph: A High-Performance Distributed Graph Database in ByteDance |
2022 |
VLDB |
5.6145466e-05 |
| 5,949 |
Hybrid Edge Partitioner: Partitioning Large Power-Law Graphs under Memory Constraints |
2021 |
SIGMOD |
5.2595857e-05 |
| 6,193 |
Incrementalization of Graph Partitioning Algorithms |
2020 |
VLDB |
5.1632545e-05 |
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| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 4,867 |
Application Driven Graph Partitioning |
2020 |
SIGMOD |
5.8651797e-05 |
| 5,017 |
TurboGraph++: A Scalable and Fast Graph Analytics System |
2018 |
SIGMOD |
5.7574792e-05 |
| 1,976 |
Towards Effective Partition Management for Large Graphs |
2012 |
SIGMOD |
9.8844201e-05 |
| 6,446 |
Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning |
2024 |
SIGMOD |
5.0588808e-05 |
| 1,968 |
An Experimental Comparison of Partitioning Strategies in Distributed Graph Processing |
2017 |
VLDB |
9.9071968e-05 |
| 5,949 |
Hybrid Edge Partitioner: Partitioning Large Power-Law Graphs under Memory Constraints |
2021 |
SIGMOD |
5.2595857e-05 |
| 3,573 |
A Scalable Distributed Graph Partitioner |
2015 |
VLDB |
6.954939e-05 |
| 8,254 |
A Study of Partitioning Policies for Graph Analytics on Large-scale Distributed Platforms |
2019 |
VLDB |
4.5491792e-05 |
| 3,839 |
Experimental Analysis of Streaming Algorithms for Graph Partitioning |
2019 |
SIGMOD |
6.7120651e-05 |
| 2,494 |
Streaming Graph Partitioning: An Experimental Study |
2018 |
VLDB |
8.6508229e-05 |