Changing Landscape from RDBMS to Operational NoSQL Systems

Big Data requirements are motivating new database management models that can process billions of data requests per second, and established relational models have been changing to keep pace. Until recently, relational database-management systems(RDBMSs) have been main stay for managing data and a lifeline for businesses that can handle millions of website requests daily. These system's popularity stems in part from their use of SQL, a declarative query language that lets users at all levels of database-management expertise manipulate and retrieve data. An RDBMS typically incorporates support for data-integrity enforcement; user authentication; role-based access control; data backup and recovery; and atomicity, consistency, isolation, and durability(ACID) transaction properties. Although RDBMSs are perfect fit in many scenarios, they are very less suitable for the big data requirements typical in modern applications. To serve modern applications, an array of alternative database-management systems has recently emerged with varied abilities for handling data volume and throughput. The main objective of this paper is to present modern database management system and how it meets current performance and scalability needs of modern applications.