Relational Database Management System ( Rdbms )

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Abstract Relational database management system (RDBMS) have used for many decades. However, these databases are facing several challenges with the requirements of many organizations like high scalability and availability. They cannot deal with huge amount of data and requests efficiently. As a result, famous organizations such as Google and Amazon shift from RDBMS to NoSQL databases. NoSQL databases have several features that overcome issues. This paper explains features, principles, and data models of NoSQL databases. However, the main focus of this paper is to compare and evaluate two of the most popular NoSQL databases which are MongoDB and Cassandra. RDBMS, NoSQL, MongoDB, Cassandra 1. Introduction In recent years with the new breed of…show more content…
If you change your application, you have to change your database schema as well. This fixed schema used by RDBMS make them impossible to quickly incorporate new types of data. Also, it is a poor fit for unstructured and semi-structured data [14, 17]. • Since queries require attributes from more than one table result in a join operation, join decreases the performance of RDBMS. Joins and locks have a negative impact on performance of RDBMS [4]. • RDBMS provide limited replication techniques. In fact, these databases are based on consistency instead of availability [14]. In order to understand NoSQL databases, chapter two will describe the most significant features of NoSQL databases for solving the above mentioned requirements. Since the relational data model is not suitable for some use cases, chapter three will explain structure and flexibility of different data models offered by NoSQL databases. Chapter four will compare two of the widely used NoSQL databases which are MongoDB and Cassandra. 2. BASE vs. ACID Both RDBMS and NoSQL databases use principles that are derived from CAP theorem. According to this theorem, following guarantees can be defined [8,12, 20]: • Consistency. All the users see the same data at any time. • Availability. When certain nodes fail, the other nodes in the system are able to continue and operate. •
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