University NoSQL Database Report: ISYS114 Assignment 3 and MongoDB

This report provides a comprehensive overview of NoSQL databases, beginning with a comparison to SQL databases and RDBMS. It explains the limitations of SQL in handling modern data needs, particularly the volume, agility, and analysis requirements of big data. The report highlights the benefits of NoSQL, such as enhanced performance, scalability, and flexible data models. It focuses on MongoDB as a prominent example of a NoSQL document database, detailing its features like easy scalability, high availability, and improved performance. The report includes an example of a MongoDB database schema for a school database, demonstrating its flexibility in storing varied data structures without predefined schemas. References are provided to support the concepts discussed.

Running head: NOSQL DATABASE AND MONGO DB
NoSQL Database and MongoDb
Name of the student:
Name of the University:
Author note:

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NOSQL DATABASE AND MONGO DB
NoSQL is basically Not Only SQL. Therefore, before proceeding with NoSQL it is
necessary to explain the concept of SQL. SQL or Structured Query Language is a database
query language used by the RDBMS. These database structures depend upon tables with row,
columns and schemas in order to organize and or retrieve necessary data or information.
A database schema is defined as the outer skeletal structure, which presents the logical view
of a complete database. The schema of these tables needs to be predefined. However, NoSQL
database on the other hand does not require to rely upon predefined structural models. They
are more flexible in terms of storage and retrieval of data. Practical experiences have over the
time showed the failure of SQL based RDBMS in coping up with the modern day needs of
data management, which is not only massive in volume and agility but also requires high end
analysis techniques to be processed (Li & Manoharan, 2013). Several large enterprises have
already switched over to NoSQL based database for the means of their business proceedings.
This is mainly due to the growing size and variability in the nature of data that comes in.
NoSQL allows them to be stored in unstructured manner. Common unstructured data that are
preferred to be stored in NoSQL database are chat messages, session data, IoT readings, large
graphical data objects such as audios and videos and many more (Moniruzzaman & Hossain,
2013).
The Benefits of using NoSQL Database are many. Enhanced performance and
scalability are the keys. Enterprise can enhance their data storage and recovery performance
through the use of NoSQL database just by adding commodity resources. This allows the
enterprises to provide the users with reliably faster experience. This can also be done with no
overhead loss for manual sharding.
According to Pokorny (2013), horizontal scale-out methodology is also used by the
NoSQL databases to make it easier for them to add or reduce the storage capacity of the
database in a quicker and non-disruptive fashion with commodity hardware. The huge cost

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NOSQL DATABASE AND MONGO DB
expense that is necessary to scale relational databases using the complex manual sharding
technique is also eradicated or eliminate with the advent of NoSQL systems. This makes
NoSQL databases highly scalable.
The implementation of fluid and flexible data models is offered by NoSQL. The
software developers can mould and leverage the data types and query options according to
their system needs (Kaur & Rani, 2013). This signifies that these can be moulded to any form
that would be the best suiting case for their application use case. This in-turn helps to store
and access data that needs not worry about the underlying database structure or schema. This
helps both the database administrator and the application to access the database in a simpler
manner and also in a faster and agile tone. These database techniques are widely used in
modern day big data handling agile development projects, where changes in software data
structures are very common.
The NoSQL database has been primarily designed to ensure high availability and
avoid the complexity of the typical relational database management system architecture,
which depends upon primary and secondary nodes to perform different operations. NoSQL
uses a distributed technique known as the masterless architecture that allows them to share
the data equally among multiple resources, thus making it available for both read and write
operations simultaneously.
Chodorow (2013), says that MongoDB is the most commonly known and widely used
open source NoSQL document database. It highlights all the key features of NoSQL like easy
scalability, high availability and enhanced performance. Unlike the tables in Oracle based
database in relational models, MongoDb works on the concept of collection as a set of
documents.

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NOSQL DATABASE AND MONGO DB
A collection is a set of documents that tend to outline a common information.
Documents are actually key-value pairs which represent a single entity in the database. The
flexibility and dynamic schema that is offered by MongoDB allows these collections to hold
various documents with a variety of fields of data (Boicea, Radulescu, & Agapin, 2012).
Below is an example of a MongoDb database that is created to serve the purpose of a school
database. A collection is created to hold the data for each student.
db.Student.insert ([
{
name: John Doe,
class: 10,
sex: ‘male’,
mains: [‘Computer Science’,’Mathematics’,’Statistics’],
additionals: ‘Graphic Design’,
practicals: [‘Computer Science’, ‘Graphic Design’]
},
{
name: Jane Doe,
class: 10,
sex: ‘female’,
mains: [‘History’,’Geography’,’Political Science’],
additionals: [‘Literature’,’Humanities’]
},
])
This example clearly shows that a Student collection is created with two different sets
of data inserted. The first has a single attribute field additionals and an array field practicals
which differs from the second document. In the second document the additionals field is an
array type and the practicals field is completely missing. This suggests the flexibility in the
use of MongoDb as it can be used to store data according to the needs of the system and there
needs not be any pre-defined database structure to guide it.

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NOSQL DATABASE AND MONGO DB
References
Boicea, A., Radulescu, F., & Agapin, L. I. (2012, September). MongoDB vs Oracle--database
comparison. In 2012 third international conference on emerging intelligent data and
web technologies (pp. 330-335). IEEE.
Chodorow, K. (2013). MongoDB: The Definitive Guide: Powerful and Scalable Data
Storage. " O'Reilly Media, Inc.".
Kaur, K., & Rani, R. (2013, October). Modeling and querying data in NoSQL databases.
In 2013 IEEE International Conference on Big Data (pp. 1-7). IEEE.
Li, Y., & Manoharan, S. (2013, August). A performance comparison of SQL and NoSQL
databases. In Communications, computers and signal processing (PACRIM), 2013
IEEE pacific rim conference on (pp. 15-19). IEEE.
Moniruzzaman, A. B. M., & Hossain, S. A. (2013). Nosql database: New era of databases for
big data analytics-classification, characteristics and comparison. arXiv preprint
arXiv:1307.0191.
Pokorny, J. (2013). NoSQL databases: a step to database scalability in web
environment. International Journal of Web Information Systems, 9(1), 69-82.