DBScholar

Back to papers

HiNGE: Enabling Temporal Network Analytics at Scale

Summary: HiNGE enables scalable temporal network analytics via a distributed graph DB storing full history and enabling past-snapshot queries. DeltaGraph, a hierarchical index, records historical traces on disk; GraphPool keeps hundreds of snapshots in memory for fast parallel analytics. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4735
Venue
SIGMOD
Year
2013
Pagerank
5.2534086e-05
Overall Rank
9,534 | 34.59%
DOI
10.1145/2463676.2465262

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{khurana_sigmod13,
        title = {{HiNGE: Enabling Temporal Network Analytics at Scale}},
        author = {Khurana, Udayan and Deshpande, Amol},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2465262},
        url = {https://dl.acm.org/doi/10.1145/2463676.2465262},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
5,039 Holistic Indexing in Main-memory Column-stores 2015 SIGMOD 6.3909067e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

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

Rank Cited Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Semantically Similar Papers