Pregelix: Big(ger) Graph Analytics on A Dataflow Engine
Summary: Iterative dataflow for scalable graph analytics on very large graphs. Pregelix uses an out-of-core capable dataflow engine to reduce memory pressure from message-passing systems, achieving up to 15x speedups vs Giraph and 35x vs GraphLab. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yingyi Bu
- 2. Vinayak Borkar
- 3. Jianfeng Jia
- 4. Michael J. Carey
- 5. Tyson Condie
Incoming Citations (Sorted by Pagerank)
Showing 18 of 18 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 5,788 | MOCgraph: Scalable Distributed Graph Processing Using Message Online Computing | 2015 | VLDB | 5.3273911e-05 |
| 2,336 | Optimizing Graph Algorithms on Pregel-like Systems | 2014 | VLDB | 9.0109891e-05 |
| 396 | One Trillion Edges: Graph Processing at Facebook-Scale | 2015 | VLDB | 0.00024424102 |
| 9,566 | Quegel: A General-Purpose System for Querying Big Graphs | 2016 | SIGMOD | 4.3254416e-05 |
| 1,408 | An Experimental Comparison of Pregel-like Graph Processing Systems | 2014 | VLDB | 0.00012133511 |
| 7,402 | A General-Purpose Query-Centric Framework for Querying Big Graphs | 2016 | VLDB | 4.7392415e-05 |
| 4 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0019005923 |