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Quegel: A General-Purpose System for Querying Big Graphs

Summary: Quegel introduces a general-purpose graph-querying system that defines queries as first-class citizens in a vertex-centric framework. It uses a novel superstep-sharing execution model to efficiently handle light-workload queries, enabling near real-time responses for tasks like point-to-point shortest paths and XML keyword search. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5170
Venue
SIGMOD
Year
2016
Pagerank
4.3254416e-05
Overall Rank
9,566 | 33.46%
DOI
10.1145/2882903.2899398

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
7,607 Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods 2025 VLDB 4.6967024e-05
10,997 Automating Vectorized Distributed Graph Computation 2024 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

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

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