SPARTex: A Vertex-Centric Framework for RDF Data Analytics
Summary: SPARTex embeds vertex-centric, user-defined graph programs as SPARQL-invocable procedures, unifying RDF querying and generic analytics. Its cost-based optimizer pipelines algorithms while minimizing communication and intermediate data I/O, achieving orders-of-magnitude speedups. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ibrahim Abdelaziz (King Abdullah University of Science and Technology)
- 2. Razen Harbi (King Abdullah University of Science and Technology)
- 3. Semih Salihoglu (Stanford University)
- 4. Panos Kalnis (King Abdullah University of Science and Technology)
- 5. Nikos Mamoulis (University of Ioannina)
BibTeX Citation
@article{abdelaziz_vldb15,
title = {{SPARTex: A Vertex-Centric Framework for RDF Data Analytics}},
author = {Abdelaziz, Ibrahim and Harbi, Razen and Salihoglu, Semih and Kalnis, Panos and Mamoulis, Nikos},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {12},
pages = {1880--1891},
doi = {10.14778/2824032.2824091},
url = {https://doi.org/10.14778/2824032.2824091},
year = {2015}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 706 | Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins | 2019 | VLDB | 0.00014622696 |
| 1,253 | Distributed Evaluation of Subgraph Queries Using Worst-case Optimal Low-Memory Dataflows | 2018 | VLDB | 0.00011316982 |
| 5,512 | Compressed Representations of Conjunctive Query Results | 2018 | PODS | 6.0867282e-05 |
| 5,514 | Fast Join Project Query Evaluation using Matrix Multiplication | 2020 | SIGMOD | 6.0866191e-05 |
| 7,478 | A Survey and Experimental Comparison of Distributed SPARQL Engines for Very Large RDF Data | 2017 | VLDB | 5.5021636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0012089097 |
| 1,498 | Asynchronous Large-Scale Graph Processing Made Easy | 2013 | CIDR | 0.00010445866 |
| 2,109 | TripleBit: a Fast and Compact System for Large Scale RDF Data | 2013 | VLDB | 9.0224381e-05 |
| 2,353 | TriAD: A Distributed Shared-Nothing RDF Engine based on Asynchronous Message Passing | 2014 | SIGMOD | 8.5756201e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,813 | gStore: Answering SPARQL Queries via Subgraph Matching | 2011 | VLDB |
| 2 | 536 | An Analytical Study of Large SPARQL Query Logs | 2018 | VLDB |
| 3 | 5,860 | Graph-Aware, Workload-Adaptive SPARQL Query Caching | 2015 | SIGMOD |
| 4 | 8,508 | Optimizing Declarative Graph Queries at Large Scale | 2019 | SIGMOD |
| 5 | 12,159 | RDFFrames: Knowledge Graph Access for Machine Learning Tools | 2020 | VLDB |
| 6 | 2,360 | Vertexica: Your Relational Friend for Graph Analytics! | 2014 | VLDB |
| 7 | 1,417 | A Distributed Graph Engine for Web Scale RDF Data | 2013 | VLDB |
| 8 | 513 | Scalable SPARQL Querying of Large RDF Graphs | 2011 | VLDB |
| 9 | 7,478 | A Survey and Experimental Comparison of Distributed SPARQL Engines for Very Large RDF Data | 2017 | VLDB |
| 10 | 7,947 | S2RDF: RDF Querying with SPARQL on Spark | 2016 | VLDB |