Thesis (M.Sc.) - Cairo University - Faculty of Computer and Information - Department of Computer Science

Nowadays the exponential growth of interconnected data is resulting from social media, computer networks and geographic applications. These applications need to store a huge amount of unstructured/semi-structured connected data that is not easily to be handled by the relational database. Graph database management systems are widely used in scenarios where the data are intensively connected. Storing and representing such connected data in a relational database is not an efficient task that is why there is a need to convert a relational database to graph database to handle such connected data. To the best of our knowledge, two main algorithms relational to graph algorithm (R2G) and Gupta{u2019}s algorithm are proposed to convert relational databases to graph databases. After studying R2G algorithm in details, we find two main problems in it. First, R2G algorithm has some limitations which are; it cannot handle multiple relationships types such as unary relationships and cannot handle associative entities (many-to-many relationships) with non-foreign key attributes. In addition to that, after step by step tracing R2G algorithm, we conclude that the given cases mentioned in R2G algorithm do not reach to the output graph database model described by R2G authors on their work

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