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 (University of California Irvine)
- 2. Vinayak Borkar (X15 Software, Inc.)
- 3. Jianfeng Jia (University of California Irvine)
- 4. Michael J. Carey (University of California Irvine)
- 5. Tyson Condie (University of California Los Angeles)
BibTeX Citation
@article{bu_vldb15,
title = {{Pregelix: Big(ger) Graph Analytics on A Dataflow Engine}},
author = {Bu, Yingyi and Borkar, Vinayak and Jia, Jianfeng and Carey, Michael J. and Condie, Tyson},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {2},
pages = {161--172},
doi = {10.14778/2732232.2732238},
url = {https://doi.org/10.14778/2732232.2732238},
year = {2015}
}
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