• V.Shanmugapriya
• Dr. D. Maruthanayagam

Big Data Movement is considered to convert unstructured and semi-structured data on the files to semantically connected documents known as the “web of data”. Resource Description Framework (RDF) represents the semantic data and a collection of such statements shapes an RDF graph. SPARQL is considered as a query language designed to query RDF data. Managing large amount of data scalable is a matter of concern for a long time. Same process is true for semantic web data. Current semantic web frameworks lack this ability. Big Data identify huge amounts of data in a connected form. Certainly, utilizing Big Data continue to be in high demand. Hence, a scalable and accessible query system requires for the availability and reusability of existing web data. RDF model is the database community using several techniques to store and query the data (RDF) in an efficient manner. But, current RDF database bear from many issues, such as poor routine behavior for querying RDF data. In this paper, a comparative analysis provides the selective RDF databases storages and a persistent access and storage of RDF graphs.

Resource Description Framework, Corporate Semantic Web, RDF Query Languages, Sesame, Jena, Semantic Web Database, Big Data

"ANALYSIS OF RESOURCE DESCRIPTION FRAMEWORK AND WEB SEMANTIC IN BIG DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.463-473, March-2019, Available :http://www.jetir.org/papers/JETIR1903I69.pdf

"ANALYSIS OF RESOURCE DESCRIPTION FRAMEWORK AND WEB SEMANTIC IN BIG DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp463-473, March-2019, Available at : http://www.jetir.org/papers/JETIR1903I69.pdf