3.1 Introduction
3.1.1 Graph Databases
A graph database represents data and relationships between this data using concepts from graph data structures like nodes, edges and properties. Nodes represents the data entities, properties represent information about the nodes and edges which connect two nodes or a node and a property represent the relationship between the connected elements. [1] Figure 3.1 Property Graph Model [2]
3.1.2 Triple stores
Triple store is a specific implementation of a graph database that is optimized for storing and retrieval of triples. A triple is a representation of data in subject-predicate-object relationship. [3]
3.2 Comparison with Relational Database systems
3.2.1 Graph Database and Relational database
Relational databases have a fixed schema. Each table is a set of rows, each of which has a fixed set of attributes. This type of structure implies that all the rows have values for all the attributes for this representation to be efficient. However, in recent years, there has been an explosion of unstructured information like tweets, product reviews, semantic web etc which cannot be represented in the structured format demanded by the tables. Moreover, it becomes very difficult to find patterns in a table as it would involve joins of many tables. In contrast, in graph databases, each element in the database contains a direct connection to its adjacent element. This information helps us to easily find the interconnectedness of the nodes and
With the advent in technology there has also been a steep increase in the crime rate. These crimes can be closely related to the graph database model. Usually the crimes have a number of sources from which they can start. These sources can be considered as the nodes of the graph. Usually these speculations lead to one or more paths which further add to the case. These are connected by edges leading to newer nodes. Thus forming a graph. The greatest similarity between the two involves eliminating formation of huge relational database. This involves the first step towards the construction of the graph database.
Abstract- This research documents a comprehensive evaluation of the emerging graph databases along with a benchmark study to compare it to the existing relational model. With the ease of the graphical representation brought in with Neo4j, we saw the opportunity to attempt getting details about the various attributes in the dataset and analyze this data to present a statistical view along with its popular counterpart, MySQL. The ultimate goal of this study is to determine whether a traditional relational database system like MySQL, can be replaced completely in production, by a graph database, such as Neo4j.
A relational database is a database that consists of a collection of tables with columns showing entities, and rows showing data. This type of database uses a primary key and foreign key. The foreign key in another table will point to the primary key of a table, and this is how tables can relate to each other. This permits for one-to-one, one-to-many, and many-to-many relationship between the data. An advantage of relational databases includes the ease of adding or modifying new tables and entities without needing to change the structure of the database already in place. Relational database have many features, including indexing, setting data type, and setting validation tests, all these help to ensure data integrity.
Relational data is when you can put data in a computer one time and it grows
Relational database contains data records that do not have a preset of relationships, permitting the user to define his or her relationship when accessing the data. Since users have much control over the data being accessed, relational databases can perform a variety of tasks. Such as defining the database; querying the database; adding, editing, and deleting data from the database; modifying the structure of the database; securing data from public access; communicating within the network; and exporting and importing data (Murthy, 2008).
A relational database is designed to comply with a term called normalization. Normalization is a process of organizing tables to minimize the redundancy in the database. The design of a relational database decreases the amount of space the database uses in a system. The relational database uses fields to help reduce redundancy in the tables. Relational designed database use the relational value in fields, an example would be a field for Book_ISBN and a field with Title_ISBN, could be limited to just one field naming the ISBN (Safari).
Metadata present a more complete picture of the data in the database than the data itself.
Firstly a relational database contains a set of tables which basically are linked collectively by the relationships between the tables. Also it is also known as reason such as a database is called relational database.
Relational databases play a major role in making many apps and programs work. They provide an easy way to store large amounts of data in a consistent, non duplicating, and maintainable way to be used by developers for analytical or software use ("Advantages of a relational database", n.d.). However, more and more applications and companies with a tremendous amount of data such as search engines, social networks, and e-commerce sites have been requiring a level of speed and scalability that relational databases can not provide ("Why NoSQL?", n.d.). NoSQL is a name given to a quickly growing type of database known as non-relational databases, which are being used to store and manage huge amounts of structured, semi-structured, and non-structured data known as "Big Data" ("Why NoSQL?" n.d.). With the advent of social networks and apps with millions of users, the rate of growth of non-structured and semi-structured data is exponential, and the value in being able to quickly traverse it, analyze it, and use it for development is also growing quickly (McGuire, Manyika, & Chui, 2012).
Relationships on a database establish a connection between two associated and logically related tables, that each have similar data. An example may be a table that contains names of certain students, and another table that contains the student's ID, the code of library books, and the dates on which each specific student checked out that particular library book. Without association of relationship on the relational database, the two tables would be independent figures with librarian lacking a method for associating student with his/ her item. The library, accordingly, would have to close down in a short period of time. The database connection, on the other hand, allows a connection to be drawn between the Student's table and the Student's instrument table (that represents the books that the student checks out).
If you change your application, you have to change your database schema as well. This fixed schema used by RDBMS make them impossible to quickly incorporate new types of data. Also, it is a poor fit for unstructured and semi-structured data [14, 17].
A relational database is a collection of data which organized into a set of tables that can be accessed in multiple ways without having to reorganize the tables’ oftenly.Relational Database was proposed by Edgar Codd around the time 1969.It has become prevalent for commercial applications. In the 20th century there were countless Relational Database System (RDBMS) take for instance: IBM.DB2 and Oracle.
Challenges: As Marcos explained: “A relational database wasn’t satisfying our requirements about performance and simplicity, due the complexity of our queries.” To address this, Marcos’ team decided to use Neo4j, a graph database, for which category Neo4j is the market leader.
Damart et al.(2007)[30] Applications of graph databases are prone to inconsistency due to interoperability issues. This raises