Modeling and Storage of XML Data as a Graph and Processing with Graph Processor

XML is a standard format for data exchange overinternet. Also huge amount of information is tagged and storedin XML format. Processing XML data has its difficulties due tothe schema centric and semi-structured nature of the majorportion of existing XML data. The data embeded tree stucturemakes it more complicated to process. XML processing usingRDBMS systems and Native XML databases like BaseX, eXist-DBhas its own limitations. Native XML databases are not suitablefor distributed processing. So they just have to bound withsingle systems resources, which are not enough for big dataprocessing. Graph databases and Graph database technologies areemmerging in the recent past. They are also suitable to process bigdata due to the extension of parallel processing features in graphdata processors. Modeling XML data as a graph and processingit with graph processors are benaficial in many contests. In thispaper the graph modleing, storage and processing possibilities ofXML data are analysed. The major graph database Neo4j andthe GraphX graph processor extension embeded with ApacheSpark distributed in-memory processing system are utilized forquerying XML data.