NoSQL: An Optimization Approach in a Stand-Alone System

Abstract

With some limiting factors of SQL databases, the NoSQL has been studied and is now a popular database that is being used by the largest companies in the world like Facebook and Google to work with the unstructured big data that they collect and manage every day. In a stand-alone application like the payroll system, the use of SQL databases also becomes a struggle especially when the collected data are growing rapidly. The normalization or query optimization has a little advantage while NoSQL solved this problem in a much better performance. In the new model, the NoSQL (MongoDB) database was designed to work with the transactional data, specifically during the read phase which must be taken from the transactional table. On the other hand, SQL (MySQL) database still works on the other tables that have stable attributes. The test was performed by using a stand-alone system over the usual application of NoSQL databases like the online distributed systems. The combined SQL and NoSQL databases conveyed significant results than that of the SQL database alone in terms of performance. It is evident that NoSQL works well with SQL. NoSQL would have been one of the best options to optimize the performance of the system. This is not only perfectly working with unstructured data in distributed systems but also bears a big advantage when applied to stand-alone systems especially when it collects and manages large volume of data.