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G-SQL: Fast Query Processing via Graph Exploration

Summary: G-SQL integrates an in-memory graph engine with an RDBMS to accelerate foreign-key-driven multiway joins via fast graph exploration. Its SQL dialect and unified cost model coordinate both engines while retaining relational storage and access methods. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11565
Venue
VLDB
Year
2016
Pagerank
5.5474529e-05
Overall Rank
7,769 | 46.70%
DOI
10.14778/2994509.2994510

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ma_vldb16,
        title = {{G-SQL: Fast Query Processing via Graph Exploration}},
        author = {Ma, Hongbin and Shao, Bin and Xiao, Yanghua and Chen, Liang Jeff and Wang, Haixun},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {12},
        doi = {10.14778/2994509.2994510},
        url = {https://doi.org/10.14778/2994509.2994510},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
2,854 Extracting and Analyzing Hidden Graphs from Relational Databases 2017 SIGMOD 8.0350257e-05
4,892 Fast In-Memory SQL Analytics on Typed Graphs 2017 VLDB 6.4574091e-05
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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.

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