NoSQL Database and MongoDb

Running head: NOSQL DATABASE AND MONGO DB
NoSQL Database and MongoDb
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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