A Comprehensive Analysis: NoSQL and Its Importance to Big Data

This report provides a comprehensive overview of NoSQL databases and their critical role in managing big data. It highlights the limitations of traditional relational database management systems (RDBMS) in handling the volume, velocity, and variety of modern data, and explains how NoSQL databases offer a more scalable and flexible solution. The report discusses various NoSQL database types, including key-value stores, document databases, graph databases, and wide-column stores, and examines their suitability for different big data scenarios. It also provides real-world examples of organizations like Facebook, Twitter, CERN and The Hut Group that leverage NoSQL databases to improve data processing, storage, and analysis, ultimately enhancing profitability and achieving a competitive advantage. The document concludes that NoSQL is essential for organizations seeking to effectively manage and leverage big data, and emphasizes the importance of selecting the right NoSQL database based on specific organizational goals and requirements. Desklib offers a wealth of resources, including past papers and solved assignments, to further assist students in their studies.

Running Head: NoSQL AND ITS IMPORTANCE TO BIG DATA
RESEARCH PAPER
[Document subtitle]

NoSQL AND ITS IMPORTANCE TO BIG DATA 1
Introduction
The relational database is built extant to the programming language of SQL, and the
organizations prefer this choice of the technology of database. The database of NoSQL supports
the design of schema, providing the potential for maximized flexibility, customization, and
scalability in comparison to the software of relational database. And this makes it suitable for the
various applications of the web, systems of content management. Basically, the technology of
NoSQL is designed for the big data. But for some users, the choices of NoSQL database are
confusing like they don’t understand that which application should be used for the big data. The
databases of NoSQL are characterized under various categories like the databases of the
document, key-value, graph and the stores of the wide column. Further, the requirement of
NoSQL is given for the better understanding and the various approaches of NoSQL for the
scenario of big data and how it is important for the big data. Further, the suitability of the
solution of NoSQL is given that can be used for the big data. Then, the example of an
organization is given which is using the database of NoSQL for the big data in order to maximize
profitability.
Need of NoSQL
NoSQL is used for the various internet organizations like Amazon, Google, etc. in order to cope
up with the challenges of RDBMS. Moreover, NoSQL uses the distant approach in order to solve
the problems of the big data. The NoSQL is required for the better working with the big data. As
it requires the flexible model of data along with the better architecture of the database (G,
Verma, & Aranha, 2016). Further, in order to proceed with the big data, the databases require
continuous availability of the database with the support of the modern transaction. HBase for
Hadoop is one of the famous databases of NoSQL which is being used by the Facebook for the
infrastructure of messaging (Özcan et al., 2014). Further, the Twitter uses HBase in order to
generate the data, storage of data, logging to monitor the data. MongoDB is also one of the
famous database of NoSQL which is being accustomed by CERN as it is a research organization
of European Nuclear for gathering the data from the “Hardon Collider” (Berg, K. L., Seymour,
T., & Goel, R. 2013). The Orbitz and similar companies use the Couchbase database of NoSQL
for the processing the data and then monitoring them.

NoSQL AND ITS IMPORTANCE TO BIG DATA 2
Approach of NoSQL for the Big Data Scenario
While deciding the solution of NoSQL for the big data, it is significant to keep the criteria of
evaluation in mind. As all the databases of NoSQL are not equal so it is important to analyze
their application for the big data of the organization. MongoDB is a database which includes the
pairs of key value (Silva et al., 2014). It has the ability to store the entrenched documents. It can
even store the binary objects to the limit of 16 MB, and if the limit exceeds then, the objects split
into various chunks which are further stored in varied files (Abramova, V., & Bernardino, J.
2013). DynamoDB is required to update the data of geo-location. The database handles the traffic
at the faster rate. There is a provision which is named as “Throughput” which is used for writes
and reads. The Cassandra is used when the organization wants to create an advertisement or a
campaign because the various users fill the timeline at a faster pace and it is very difficult to
achieve the insights from that information by using other databases than the NoSQL. The
databases of NoSQL are based on the RAM, and this is the main reason that NoSQL database
works much better than the variety of RDBMS (Moniruzzaman et al., 2013).
Critical Nature of NoSQL to Manage the Big Data
When the industry of technology experiences a shift in the development of hardware, there is a
point of inflection. The node's set in the form of a cluster are used by the various giants like IBM
and Oracle in the form of clusters in order to offer a scaling ability that helps the users to adjoin
nodes in order to carry the load (Cuzzocrea et al., 2011). The organizations are depending on the
big data in order to accomplish their mission. The organizations are using the database of
NoSQL for the emerging of data. The developers require a database which is flexible in nature so
that they can accommodate the type of data easily ("NoSQL importance," 2016). Most of the
data is semi-structured and unstructured, and the data is efficiently stored by the developers.
Therefore, the approach of schema-based is not suitable for the relational database, and it makes
it difficult to implement the new data types effectively. The technology of NoSQL is the solution
which is available to meet the desired needs of the organization in order to provide the flexibility
and scalability of the solutions for accessing and managing the data (Henderson et al., 2016).
Further, the database of NoSQL is the technology driven through the cloud computing, big data
and the web. NoSQL helps in overcoming the various challenges which the organizations are
facing from the last 40 years by using traditional RDBMS. The database of NoSQL is the

NoSQL AND ITS IMPORTANCE TO BIG DATA 3
alternative for the database of SQL and it doesn’t require any type of fixed schema tables unlike
the database of SQL. Moreover, NoSQL is defined as the structured storage that contains the
relational database like the subset. It covers multiple databases which have different type of
storage model.
Examples of NoSQL Deployment for Big Data
 The applications of the web need the profile of the users and the capability to log in. the
database of NoSQL helps in storing the IDs, preferences, additional information, etc. of
the user so that the application can look up the user and certify the access. For the
effective functionality of the web application, the attributes of NoSQL are significant
("Data Management et al., 2016).
 The companies of e-commerce depend on the swings of the seasons of the industry. The
users face challenges while purchasing gifts at the last moment and this develops the
spike. Further, NoSQL is used in order to handle the spike without even investing more
in the infrastructure. NoSQL increases the activity of the user and scales down according
to the subsiding of the user activity. For example, The Hut Group.
Conclusion
NoSQL offers the great solution for the requirements of the big data where the request of
velocity and volume are high. It is very important to analyze the database of NoSQL depending
on the goals and requirement of the organization. Further, it can be easily understood that
NoSQL is very important for the big data because the traditional databases like RDBMS are no
more suitable for the problems of big data in order to overcome the issues and maximizing the
profitability of the organization. Therefore, the paper helps in understanding all the relevant
information of the NoSQL database and how it is important to big data. Further, the importance
is explained with the help of some example of some organizations which deploy NoSQL for the
big data in order to maximize profitability and achieving the sustainable competitive advantage.

NoSQL AND ITS IMPORTANCE TO BIG DATA 4
REFERENCES
Abramova, V., & Bernardino, J. (2013, July). NoSQL databases: MongoDB vs cassandra.
In Proceedings of the International C* Conference on Computer Science and Software
Engineering (pp. 14-22). ACM.
Berg, K. L., Seymour, T., & Goel, R. (2013). History Of Databases. International Journal of
Management & Information Systems (Online), 17(1), 29.
Cuzzocrea, A., Song, I. Y., & Davis, K. C. (2011, October). Analytics over large-scale
multidimensional data: the big data revolution!. In Proceedings of the ACM 14th international
workshop on Data Warehousing and OLAP (pp. 101-104). ACM.
Data Management/Data Warehousing information, news, and tips - SearchDataManagement.
(2016). Searchdatamanagement.techtarget.com. Retrieved 14 November 2016, from
http://searchdatamanagement.techtarget.com/
G, L., Verma, G., & Aranha, D. (2016). Learn job skills from Industry Experts Online | DeZyre.
DeZyre. Retrieved 14 November 2016, from https://www.dezyre.com
Henderson, T., Smith, M., Brown, B., & Heisler, Y. (2016). Welcome to Network World.com.
Network World. Retrieved 14 November 2016, from http://www.networkworld.com/
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.
NoSQL importance. (2016). Retrieved 14 November 2016, from https://www.quora.com
Özcan, F., Tatbul, N., Abadi, D. J., Kornacker, M., Mohan, C., Ramasamy, K., & Wiener, J.
(2014, June). Are we experiencing a big data bubble?. In Proceedings of the 2014 ACM
SIGMOD international conference on Management of data (pp. 1407-1408). ACM.
Silva, L. A. B., Beroud, L., Costa, C., & Oliveira, J. L. (2014, June). Medical imaging was
archiving: A comparison between several NoSQL solutions. In IEEE-EMBS International
Conference on Biomedical and Health Informatics (BHI) (pp. 65-68). IEEE.