Book Image

NoSQL Data Models

By : Olivier Pivert
Book Image

NoSQL Data Models

By: Olivier Pivert

Overview of this book

Big Data environments are now to be handled in most current applications, this book addresses the latest issues and hurdles that are encountered in such environments. The book begins by presenting an overview of NoSQL languages and systems. Then, you’ll evaluate SPARQL queries over large RDF datasets and devise a solution that will use the MapReduce framework to process SPARQL graph patterns. Next, you’ll handle the production of web data, generate a set of links between two different datasets and overcome different heterogeneity problems. Moving ahead, you’ll take the multi-graph based approach to overcome challenges faced by the RDF data management community. Finally, you’ll deal with the flexible querying of graph databases and textual data management. By the end of this book, you’ll have gathered essential information on big data challenges faced by NoSQL databases.
Table of Contents (11 chapters)
List of Authors
End User License Agreement

5.2. Related work

In order to efficiently answer SPARQL queries, many stores and APIs inspired by the relational model were proposed [ERL 12, BRO 02, NEU 10, CAR 04]. x-RDF-3X [NEU 10], inspired by modern RDBMS, representing RDF triples as a large three-attribute table. The RDF query processing is boosted using an exhaustive indexing schema coupled with statistics over the data. Also, Virtuoso [ERL 12] strongly exploits the RDBMS mechanism in order to answer SPARQL queries. Virtuoso is a column-store based system that uses sorted multi-column column-wise compressed projections. Furthermore, these systems build table indexing using standard B-trees. Jena [CAR 04] supplies API for manipulating RDF graphs. Jena exploits multiple-property tables that permit multiple views of graphs and vertices, which can be used simultaneously.

The database community has recently started to investigate RDF stores based on graph data management techniques [DAS 14, ZOU 14b, KIM 15]. The work in [DAS 14] addresses...