We are now in an era where the technology has rapidly become democratized. The restrictions of relational databases to address the requirements of contemporary application domains, such as semantic web and social networking, where data has an inherited graph structure underlying in it, leads to the development of new technology called Graph Databases. Graph databases can be defined as those in which data structures for the schema and instances are modelled as graphs and data manipulation is expressed by graph-traversal operations. On the other hand, the Complexity involved in the relational model to process large queries quickly involving complex join operations leads to the development of the Join-Core. The Join Core consists of a set of tables that store the relationships of data. With join core, no relations or intermediate results need to be retrieved, generated, or transferred, only query results need to be transferred over the networks. In this study, an overview and comparison of current graph database models like AllegroGraph, FlockDB, Neo4j, Sones, DEX etc. is presented. The comparison shows that Neo4j is the most popular and highly recommended among all graph databases. Also the experimental results of Join Core against Neo4j graph database shows that join core performance is more efficient that Neo4j when the query has complex join operations involved in it.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-3046 |
| Date | 01 December 2016 |
| Creators | Narne, Kavya |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses |
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