… Spartex, a distributed framework for rich RDF data analytics. Spartex allows users to write
queries that combine declarative SPARQL with procedural code for generic graph processing. …

… map RDF data to a … graph model to represent RDF data, and utilizing graph database
techniques (such as a structure-aware index and a graph matching algorithm) to address RDF data …

… In this paper, we present a survey of 22 state-of-the-art systems that cover the entire spectrum
of distributed RDF data processing and categorize them by several characteristics. Then, …

… Multiple work have been done on implementation of distributed and scalable graph
databases. Furthermore, several large scale RDF stores has been described in recent research. …

… Multiple work have been done on implementation of distributed, scalable graph databases.
Furthermore, several large scale RDF stores has been described in recent research. It …

… domain, could require large scale extraction operation that … data type (ADT) [6], we define
the abstract RDF graph data … concrete data structure used to represent and expose the graph. …

… a workloaddriven data fragmentation for distributed RDF graph sys… RDF graph to reduce
the communication cost. As selecting all FAPs could lead to expensive space cost owing to data …

… , query, and process largescale semantic web data in a distributed method. The remaining …
semantic web data including RDF, RDFS and SPARQL. It also has the structure of RDF graph …

… without considering any semantics and graph structure embedded in RDF graph, which
leads to … ; distributed; basic graph pattern matching; large scale RDF graphs; MapReduce …

… However, this process is both data-… large scale RDF datasets. In this paper, we presented
DistLODStats, a novel software component for distributed in-memory computation of RDF …