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Record link: 
http://hdl.handle.net/20.500.12708/55095
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Title: 
Benchmarking Database Systems for Graph Pattern Matching
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Citation: 
Pobiedina, N., Rümmele, S., Skritek, S., & Werthner, H. (2014). Benchmarking Database Systems for Graph Pattern Matching. In Database and Expert Systems Applications 25th International Conference, DEXA 2014, Munich, Germany, September 1-4, 2014. Proceedings, Part I (pp. 226–241). Springer Verlag. https://doi.org/10.1007/978-3-319-10073-9_18
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Publisher DOI: 
10.1007/978-3-319-10073-9_18
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Authors: 
Pobiedina, Nataliia 
Rümmele, Stefan 
Skritek, Sebastian 
Werthner, Hannes 
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Organisational Unit: 
E194-04 - Forschungsbereich E-Commerce 
E192-02 - Forschungsbereich Databases and Artificial Intelligence 
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Published in: 
Database and Expert Systems Applications 25th International Conference, DEXA 2014, Munich, Germany, September 1-4, 2014. Proceedings, Part I 
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DOI of the book: 
10.1007/978-3-319-10073-9
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Date (published): 
2014
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Event name: 
DEXA - International Conference on Database and Expert System Applications 
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Event date: 
4-Sep-2006 - 8-Sep-2006
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Event place: 
Krakow, EU
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Number of Pages: 
16
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Publisher: 
Springer Verlag
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Peer reviewed: 
Yes
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Abstract: 
In graph pattern matching the task is to find inside a given graph some specific smaller graph, called pattern. One way of solving this problem is to express it in the query language of a database system. We express graph pattern matching in four different query languages and benchmark corresponding database systems to evaluate their performance on this task. The considered systems and languages are the relational database PostgreSQL with SQL, the RDF database Jena TDB with SPARQL, the graph database Neo4j with Cypher, and the deductive database Clingo with ASP.
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Project title: 
SEE: SPARQL Evaluation and Extensions (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds) 
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Research Areas: 
Business Informatics: 100%
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Science Branch: 
Informatik
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Appears in Collections:
Conference Paper

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