Column-store support for RDF data management

Abstract

This paper reports on the results of an independent evaluation of the techniques presented in the VLDB 2007 paper "Scalable Semantic Web Data Management Using Vertical Partitioning", authored by D. Abadi, A. Marcus, S. R. Madden, and K. Hollenbach [1]. We revisit the proposed benchmark and examine both the data and query space coverage. The benchmark is extended to cover a larger portion of the query space in a canonical way. Repeatability of the experiments is assessed using the code base obtained from the authors. Inspired by the proposed vertically-partitioned storage solution for RDF data and the performance figures using a column-store, we conduct a complementary analysis of state-of-the-art RDF storage solutions. To this end, we employ MonetDB/SQL, a fully-functional open source column-store, and a well-known-for its performance-commercial row-store DBMS. We implement two relational RDF storage solutions-triple-store and vertically-partitionedin both systems. This allows us to expand the scope of [1] with the performance characterization along both dimensions-triple-store vs. vertically-partitioned and row-store vs. column-store-individually, before analyzing their combined effects. A detailed report of the experimental test-bed, as well as an in-depth analysis of the parameters involved, clarify the scope of the solution originally presented and position the results in a broader context by covering more systems.

Ultrawrap: SPARQL execution on relational data

“…The number of self-joins in the plan corresponds to the number of properties co-located in a table. The phenomenon is reminiscent of the debate concerning the use of row-stores vs. column stores [12,21,44,47]. Consideration of rowstores vs. column-stores is outside the scope of this paper.…”

“…Consideration of rowstores vs. column-stores is outside the scope of this paper. Nevertheless, we note that there is debate within the community on the use of row-stores or column-stores for native RDF data and our measurements may help ground that debate [12,21,44,47].…”

RDFProv: A relational RDF store for querying and managing scientific workflow provenance

“…Our attention also catch column-oriented databases [7,95], which can be customized for provenance management, and provenance reduction techniques [28], which can be used to decrease storage requirements via duplicate elimination and provenance inheritance. Finally, we would like to consider querying and managing scientific workflow provenance in distributed environments with multiple computing nodes to enable processing of huge datasets with billions of triples.…”

A Cloud-Based Platform for Democratizing and Socializing the Benchmarking Process

“…In addition, other researchers can exploit this available software artifacts as a valuable starting point to evaluate and assess the significance of their own proposed contribution. One of the interesting examples for the value of such independent evaluation studies is the study of Sidirourgos et al [39] where they have reported about an independent assessment of the published result by Abadi et al in [4] which described an approach for implementing a vertically partitioned DBMS for Semantic Web data management. The outcomes of this independent assessment revealed many interesting aspects.…”

“…For instance, in [4] Abadi et al reported that the performance of binary tables is superior to that of the clustered property table for processing RDF queries while Sidirourgos et al [39] reported that even in columnstore database, the performance of binary tables is not always better than clustered property table and depends on the characteristics of the data set. In addition, the experiments of [4] reported that storing RDF data in column-store database is better than that of row-store database while [39] experiments have shown that the gain of performance in column-store database depends on the number of predicates in a data set. A main lesson from this example is that we cannot really be sure that published research results are accurate and comprehensive even if they were reported by the best scientists and went through the most rigorous peer review process.…”