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DREAM: Distributed RDF Engine with Adaptive Query Planner and Minimal Communication

Summary: DREAM partitions SPARQL queries, not RDF data, avoiding intermediate shuffles and enabling pattern matching. An adaptive, graph-based, rule-oriented planner and a new cost model distribute work across clusters and outperform popular RDF systems. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11365
Venue
VLDB
Year
2015
Pagerank
6.0014798e-05
Overall Rank
6,029 | 58.64%
DOI
10.14778/2735508.2735516

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{hammoud_vldb15,
        title = {{DREAM: Distributed RDF Engine with Adaptive Query Planner and Minimal Communication}},
        author = {Hammoud, Mohammad and Rabbou, Dania Abed and Nouri, Reza and Beheshti, Seyed-Mehdi-Reza and Sakr, Sherif},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {6},
        pages = {654--665},
        doi = {10.14778/2735508.2735516},
        url = {https://doi.org/10.14778/2735508.2735516},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
2,973 Functional Dependencies for Graphs 2016 SIGMOD 7.9083516e-05
7,777 S2RDF: RDF Querying with SPARQL on Spark 2016 VLDB 5.5461212e-05
7,798 A Survey and Experimental Comparison of Distributed SPARQL Engines for Very Large RDF Data 2017 VLDB 5.542286e-05
11,944 Stylus: A Strongly-Typed Store for Serving Massive RDF Data 2018 VLDB 5.093636e-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.

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