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Graph Data Management Systems for New Application Domains

Summary: Survey of graph data management for large-scale graphs; taxonomy by data/computation models, with representations (dense/sparse native, triples, relational) and core queries (reachability, neighborhoods, updates). Maps models to concrete systems and workloads; contrasts declarative, optimizable query-driven approaches (Neo4j/Horton) with procedural ones (Pregel), highlighting optimization implications. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10242
Venue
VLDB
Year
2011
Pagerank
4.6326563e-05
Overall Rank
7,865 | 45.29%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
4,830 Systems for Big-Graphs 2014 VLDB 5.8924342e-05
6,847 TriAL for RDF: Adapting Graph Query Languages for RDF Data 2013 PODS 4.9089877e-05
7,775 Graph Querying Meets HCI: State of the Art and Future Directions 2017 SIGMOD 4.653773e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank Cited Paper Year Venue Pagerank
4 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0019005923
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