Outcome Analysis of Relational and Graph Databases

  Shubhangi S. Marudkar,  Harsha R. Vyawahare

Getting together enormous measures of complex data like information and learning is exceptionally regular these days. This requires the need to represent, store and manupulate complex data. From most recent three decades, the relational databases are being utilized as a part of numerous associations of different natures, for example, Instruction, Wellbeing, Business and in numerous different applications. Conventional databases indicate colossal execution and are intended to deal with organized information with ACID (Atomicity, Consistency, Isolation, Durability) property to oversee information uprightness but relational databases can't process appropriately and oversee substantial measure of information proficiently. Presently a day's advancements are moving towards movement, UI, Web of things, Program based IDEs and so on. These advancements require constant reaction and vast information store. A conventional database framework recovers and oversees database in a forbidden shape, yet in current situation of conveyed huge scale database those databases does not perform well. To conquer the impediments of customary databases, and to cover the necessities of current applications has lead the improvement of new database advances, for example, graph databases. We are showing an orderly examination of relational and graph database models, for that we are utilizing MySQL and Neo4j. Here we will think about the reasonableness of two classes of databases that is Relational database and graph database for putting away and questioning datasets. We will report aftereffects of estimations of scalability, query performance, and ease of query expression utilizing synthetic datasets.

Keywords- neo4j; Graph database; scalability; query performance; query expression.

Unique Identification Number - IJEDR1704129
Page Number(s) - 786-791
Pubished in - Volume 5 | Issue 4 | November 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Shubhangi S. Marudkar,  Harsha R. Vyawahare,   "Outcome Analysis of Relational and Graph Databases", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 4, pp.786-791, November 2017, Available at :http://www.ijedr.org/papers/IJEDR1704129.pdf