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Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch

Summary: Cross-category empirical study of full-graph vs. mini-batch GNN training systems, advocating time-to-accuracy—not epoch time—as the fair metric. Across datasets, models, and configurations, mini-batch converges faster and achieves similar or higher accuracy, refuting sampling concerns. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h9152d63dc7c278f8
Venue
VLDB
Year
2025
Pagerank
5.0480912e-05
Overall Rank
10,263 | 31.03%
DOI
10.14778/3717755.3717776
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{bajaj_vldb25,
        title = {{Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch}},
        author = {Bajaj, Saurabh and Son, Hojae and Liu, Juelin and Guan, Hui and Serafini, Marco},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {4},
        pages = {1196--1209},
        doi = {10.14778/3717755.3717776},
        url = {https://doi.org/10.14778/3717755.3717776},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,948 BiLink: Bidirectional Meta-paths for Link Discovery in Billion-Scale Heterogeneous Graphs 2026 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
211 AliGraph: A Comprehensive Graph Neural Network Platform 2019 VLDB 0.00024805216
1,033 AGL: A Scalable System for Industrial-purpose Graph Machine Learning 2020 VLDB 0.00012391866
1,134 SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks 2022 VLDB 0.0001188789
1,772 ByteGNN: Efficient Graph Neural Network Training at Large Scale 2022 VLDB 9.6746467e-05
2,281 NeutronStar: Distributed GNN Training with Hybrid Dependency Management 2022 SIGMOD 8.7021423e-05
2,506 DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU 2023 SIGMOD 8.3735089e-05
2,598 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD 8.238044e-05
4,855 NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments 2024 VLDB 6.377545e-05
4,899 Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective 2024 VLDB 6.3628105e-05
6,927 HongTu: Scalable Full-Graph GNN Training on Multiple GPUs 2023 SIGMOD 5.6399587e-05
7,511 ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling 2023 SIGMOD 5.5044293e-05
Previous Page 1 / 1 Next

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