NoSQL and its importance to Big Data

Write a Research paper on the topic, “NoSQL and its importance to Big Data”.

The relational database is built extant to the programming language of SQL, and the organizations prefer this choice of the technology of the database. The database of NoSQL supports the design of the schema, providing the potential for maximized flexibility, customization, and scalability in comparison to the software of the 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 big data. But for some users, the choices of the 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 a better understanding and the various approaches of NoSQL for the scenario of big data and how it is important for 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 a distant approach in order to solve the problems of big data. NoSQL is required for better working with 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 Facebook for the infrastructure of messaging (Özcan et al., 2014). Further, Twitter uses HBase in order to generate the data, storage of data, logging to monitor the data. MongoDB is also one of the famous databases of NoSQL which is being accustomed by CERN as it is a research organization of European Nuclear for gathering the data from the “Hadron Collider” (Berg, K. L., Seymour, T., & Goel, R. 2013). The Orbitz and similar companies use the Couchbase database of NoSQL for processing the data and then monitoring them.

The 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 that 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 a faster rate. There is a provision which is named as “Throughput” which is used for writes and reads. 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 the 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 nodes 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 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 that 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 that 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 technology-driven through 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 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 that have a 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.

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.
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