As the volume of data generated by different applications has experienced tremendous and unprecedented growth across different categories of applications in today's society, the need for high-performance database management systems has also increased significantly. Two of the most commonly used database types are SQL databases and NoSQL databases. SQL-based databases operate on the relational model, which is based on a predefined schema (the way the data is organised) and guarantees the consistency of data through strict adherence to the ACID properties (the rules governing the treatment of data)[1]. SQL databases are well suited for applications that require structured data and complex queries. In contrast, NoSQL databases operate with a dynamic schema (flexible ways to organise data), so they can support large volumes of either unstructured or semi-structured data. Successful implementation of NoSQL has also proven able to provide extreme horizontal scalability (expanding the power of a computer by adding more computers), and have proven reliable, yielding high availability, which makes NoSQL a great choice for applications requiring both big data and real-time processing needs [2]. This paper will evaluate and compare the respective benefits and weaknesses of both SQL databases and NoSQL databases, in terms of their data models, scaling characteristics, consistency, performance, and real-world use cases. Each of the two database types will be studied holistically. The study will result in recommendations regarding how organisations can make the best use of either SQL databases or NoSQL databases [3].
SQL Database, NoSQL Database, Relational Database, Non-Relational Database, Data Models, Scalability, ACID, BASE, Big Data, Database Management Systems.
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