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By:Barack Karavani
Published on 2015 by

As applications have evolved to be more robust and complex, so has their data. Application's have almost entirely become soley dependent on their data. Data powers our applications and has helped them evolve to be the feature-full products we've come to love. In addition to the more complex requirements of software, developers have also began shifting their approach for creating applications from the existing waterfall model. Historically, the problem of data has been solved through the use of one of the many flavors of relational databases such as MySQL, PostgreSQL, and Oracle. But, given how our applications and their data is evolving, the existing relational databases may no longer be the |one size fits all'' solution that they have been before. A new breed of databases not based on the existing relational model have started to catch the attention of developers. These databases have been categorized as Not Only SQL databases or NoSQL databases. NoSQL databases include distributed key-value stores such as Redis and Riak, document-oriented databases such as MongoDB and CouchDB, and graph databases such as Neo4j. As the requirements of our applications have shifted, from the amount of data stored, agile software development, and requirements for availability, NoSQL databases have gradually become the more popular solution for storing data. Each type of database has proven to be beneficial for a set of use cases. Distributed key-value stores such as Redis have become popular to be used as an intermediate high availablity and performance data stores. Documented-oriented databases such as MongoDB have also become popular due to their rich feature-set, ability to shard data, and schema-less nature which allows developers to focus on applications without worrying about schema. Unfortunately, outside of their use cases, document and distributed key-value store databases, haven't helped in the ability to solve complex relationships. A use case exists for databases that easily allow developers to model complex relationships amongst data. While the original solution to this problem may have been relational databases, one may argue that relational databases aren't entirely relational and do not lend themselves to modeling complex relationships. While relational database have partially solved this problem, a complete solution now exists with graph databases such as Neo4J. Graph databases combine the schema-less nature of other NoSQL databases but relationships are first class citzens and can easily be created to model real-world data. Given this well defined use case and a glaring problem that needs to be solved, this thesis will explore the use of a graph database for a non-trivial application. The application that will be examined is the Electronic Assesment System (EAS) developed by the Pioneering Technology Group (PTG) at California State University Northridge (CSUN). EAS is one of the premier applications developed by PTG which will be used by CSUN professors, students, and staff to assess student learning through their higher educational careers while attending CSUN. This thesis will explore, for the same set of data containing complex relationships, how would data be modelled in a graph database, how do the queries between each database compare to one another, and how it would have helped aid development within an Agile environment.

This Book was ranked at 4 by Google Books for keyword Relational Databases.

Book ID of The Case for the Graph Database's Books is 9TGZnQAACAAJ, Book which was written byBarack Karavanihave ETAG "TCvkKgZynz0"

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