An evaluation of triple-store technologies for large data stores

被引：0

作者：

Rohloff, Kurt ^{[1
]}

Dean, Mike ^{[1
]}

Emmons, Ian ^{[1
]}

Ryder, Dorene ^{[1
]}

Sumner, John ^{[1
]}

机构：

[1] BBN Technol, Cambridge, MA 02138 USA

来源：

ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS 2007: OTM 2007 WORKSHOPS, PT 2, PROCEEDINGS | 2007年 / 4806卷

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a comparison of performance of various triple-store technologies currently in either production release or beta test. Our comparison of triple-store technologies is biased toward a deployment scenario where the triple-store needs to load data and respond to queries over a very large knowledge base (on the order of hundreds of millions of triples.) The comparisons in this paper are based on the Lehigh University Benchmark (LUBM) software tools. We used the LUBM university ontology, datasets, and standard queries to perform our comparisons. We find that over our test regimen, the triple-stores based on the DAML DB and BigOWLIM technologies exhibit the best performance among the triple-stores tested.

引用

页码：1105 / 1114

页数：10

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