Study on Graph Databases | Assignment

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Contents
Graph databases........................................................................................................ 3
ERD............................................................................................................................ 5
References................................................................................................................. 5

Graph databases
A graph can be defined as a collection of nodes or vertices which are joined
together using edges. Each node is a representation of some piece of information
while the edge is the connection between two vertices. Using the concept of graphs,
we can now define a graph database (Clarke, 2019).
A graph database is a database engine that models’ nodes and edges in the
relational graph as first-class entities allowing representation of complex
interactions between data in a form that is more natural and often allowing a closer
fit to the real-world data that is being worked on (Domenjoud & Vial, 2012). Graph
databases are schema-less thus allowing flexibility of a key/value store or document
database but at the same time supporting relationships in a similar fashion of
traditional relational databases. This means there is more flexibility in the how the
data model is defined thus leading to faster iteration in projects. A graph database
meets the following criteria;
 Optimization of storage to represent data as a graph is done through storing
data in node/vertices and edges.
 Optimization of storage to traverse the graph without using an index when
the edges are followed. A graph database undergoes optimization for queries
to leverage proximity of data by starting from one or more root nodes rather
than using global queries.
 Flexibility in the data model for some specific solutions. This means there is
no need to declare data types for nodes/vertices or edges like it’s the case for
traditional relational databases.
Traversal in graph databases is the process of visiting nodes making up the graph
database. Traversal in graph databases is much quicker as compared to JOIN
operations in relational databases because in graph databases edges make it easy
to retrieve information from the nodes. Traversal in a graph database only takes to
account data that is needed without having to group the entire set of data like in
the case of traditional relational databases.
Why use Graph Databases
Graph databases are considered over traditional relational databases because of
the following reasons;
 Speed – Graph databases are faster than traditional databases as
demonstrated by an experiment done by Aleska Vukotic and Jonas Partner
which used social networks. The experiment involved querying a Neo4J
database and MySQL database each with a million users. The following tables
shows the time each database took (Ogidan, 2018).