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Benchmarking of Relational and NoSQL

Question:

Discuss about the Benchmarking of Relational and NoSQL.

Answer:

Introduction:

NoSQL commonly known as Not Only SQL Database, is an approach that helps to accommodate wide range of data models that includes key-value, columnar, graphs, as well as document format.

Not Only SQL is basically an alternative to the traditional Relational Database in which the information is placed in the tables, and the data schema is designed carefully before building the database (Liao et al. 2016). Specifically, when the work is done on large sets of data that are distributed, then databases of NoSQL are used.

NoSQL means implementing the database for designing the software solution or a product (Bugiotti et al. 2014). Not Only SQL is used when there are multiple storage systems that are can be used based on the requirement. NoSQL was previously a hashtag that was chosen to meet up and discuss the new databases. No SQL came from Polyglot Persistence.

Not only SQL differs from traditional relational database mainly in four different sectors. The four areas where they can be differentiated is discussed below.

  • Data Models: In NoSQL, the schema is not to be defined to build the application. The database of NoSQL helps to make the application even without defining the schema that is not possible in relational database (Fiannaca and Huang 2015). The schema is to be defined first in RDMS before adding or deleting data in the database. For updating the data in NoSQL or changing the requirements of the database, predefined schema is not required.
  • Data Structure: In relational databases, the data is to be structured and the relation between them is to be shown clearly (Noel et al. 2015). On the other hand, NoSQL databases usually handles data that are unstructured.
  • Scaling: The NoSQL database is much cheaper to scale than the relational database. This is because in NoSQL space can be added by scaling commodity and cheap servers, but RDMS requires a particular server for hosting the database. For scaling purpose, expensive and bigger servers are needed.
  • Development Model: The database of NoSQL is open sourced and the relational databases are closed source along with licensing fees. The NoSQL database does not requires any huge investments.

Application of NoSQL on DreamHome

Since, the NoSQL database does not require any particular web application file format (Gadepally et al. 2015). The database of NoSQL is compatible with different web applications. So, NoSQL can be used in DreamHome Database to make the structure more compatible. Any type of file format can be used, processed or can be integrated in web application using the NoSQL. In the DreamHome Database, NoSQL could be used because the storage as well as the retrieval of the system is different from the relations that are used in relational database.

If the database of DreamHome could be done on NoSQL, then large amount of data sets could be used as there is no boundary for data. Handling a real life application of NoSQL is much easier than relational databases.

References

Bugiotti, F., Cabibbo, L., Atzeni, P. and Torlone, R., 2014, October. Database design for NoSQL systems. In International Conference on Conceptual Modeling (pp. 223-231). Springer, Cham.

Fiannaca, A.J. and Huang, J., 2015. Benchmarking of Relational and NoSQL Databases to Determine Constraints for Querying Robot Execution Logs. Computer Science & Engineering, University of Washington, USA, pp.1-8.

Gadepally, V., Bolewski, J., Hook, D., Hutchison, D., Miller, B. and Kepner, J., 2015, May. Graphulo: Linear algebra graph kernels for NoSQL databases. In Parallel and Distributed Processing Symposium Workshop (IPDPSW), 2015 IEEE International (pp. 822-830). IEEE.

Liao, Y.T., Zhou, J., Lu, C.H., Chen, S.C., Hsu, C.H., Chen, W., Jiang, M.F. and Chung, Y.C., 2016. Data adapter for querying and transformation between SQL and NoSQL database. Future Generation Computer Systems, 65, pp.111-121.

Noel, S., Harley, E., Tam, K.H. and Gyor, G., 2015. Big-Data Architecture for Cyber Attack Graphs Representing Security Relationships in NoSQL Graph Databases.

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