Relational And Non Relational Database Model Essay

A relational database is a database that consists of a collection of tables with columns showing entities, and rows showing data. This type of database uses a primary key and foreign key. The foreign key in another table will point to the primary key of a table, and this is how tables can relate to each other. This permits for one-to-one, one-to-many, and many-to-many relationship between the data. An advantage of relational databases includes the ease of adding or modifying new tables and entities without needing to change the structure of the database already in place. Relational database have many features, including indexing, setting data type, and setting validation tests, all these help to ensure data integrity.

Coronel, C. (2013). Database Systems: Design, Implementation, and Management, Tenth Edition. Mason, Ohio, United States: Cengage Learning.

Relational database contains data records that do not have a preset of relationships, permitting the user to define his or her relationship when accessing the data. Since users have much control over the data being accessed, relational databases can perform a variety of tasks. Such as defining the database; querying the database; adding, editing, and deleting data from the database; modifying the structure of the database; securing data from public access; communicating within the network; and exporting and importing data (Murthy, 2008).

In order to overcome these limitations, a new database model known as Not Only SQL (NoSQL) database emerged with a set of new features. The main objective of NoSQL is not to discard SQL, but to be used as an alternative database data model for new features [1] [2] [3]. NoSQL database increases the performance of relational databases by a set of new characteristics and advantages. In contrast to relational databases, NoSQL databases introduced an additional feature that provides flexible and horizontal scalability and taking advantage of new clusters. The rise of NoSQL provides cost-effective management of data in modern web applications. With its new features, NoSQL can be used with applications that have a large transaction, and require low-latency access to huge datasets, service availability while

The idea of relational database was first introduced by E.F.Codd at IBM in 1970. It is a kind of computer database in which data is stored in Relations and is represented in the form of tables with rows and columns. Databases can vary in sizes, ranging from very small and simple to very large and complex ones. Database users can access the data practically in an unlimited number of ways. Relational databases help in finding the information in a quick and efficient manner that one is looking for.Today many popular databases use the model of relational database.

Abstract – With companies such as Facebook and Google producing large volumes of data, known as Big Data, the popularity of NoSQL databases has risen in the past decade as traditional relational databases cannot handle the vast amount of data as it was not designed to effectively manage such a large data collection. The following research paper gives an introduction to non-relational databases otherwise known as NoSQL. It defines what a NoSQL database is, the origins of its existence and the various types of NoSQL databases. It goes on to discuss the advantages and disadvantages of non-relational databases and the reason companies in the past decade are selecting to implement these databases over traditional relational databases.

Metadata present a more complete picture of the data in the database than the data itself.

Personal privacy today is a controversial and complex topic, which is influenced by a number of factors. There is an integral role that databases play in this highly debated topic. The fact that many people now carry out their transactions electronically is another important factor. There is also pressure on personal privacy for increased national security around the world to combat terrorism. In addition, personal privacy is even threatened by commercial factors and the Internet.

In 1977, Larry Ellison, Bob Miner, and Ed Oates founded System Development Laboratories. After being inspired by a research paper written in 1970 by an IBM researcher titled “A Relational Model of Data for Large Shared Data Banks” they decided to build a new type of database called a relational database system. The original project on the relational database system was for the government (Central

Then came relational database, Edgar Codd, who worked for the IBM’s San Jose Research Laboratory came up with a revolutionary database that would change the way information was stored. He used a “A Relational Model of Data for Large

When we design a database for a relational system, the main objective in the development of a logical data model is to create an accurate representation of the data its relationship and constraints. The data should be split in different tables, which can then be joined together based on their relations with each other and the data found in each one of them. These tables should therefore be designed well to save on space and ensure that cases on data inconsistency are eliminated. Another aspect, which will be saved on, is space that is occupied by repetitive data.

The relational model, which uses predefined tabular relations to store data, has remained the preeminent model for data storage since it was first implemented in the early 1980s. However, due to the proliferation of the Internet, today data flows in and out of organizations quickly, and most of this data is in a semi-structured state that is designed for communication over http. It is difficult to fit this complex data into a flat two dimensional array. For that reason, it is imperative that companies have the ability to store data in a semi-structured format compatible with modern network communications as well as various platforms and devices. The market has realized this and responded with document stores that support formats,

The modern RDBMS advancements are not capable of supporting unstructured information with ideal space necessity. The plan winds up plainly mind-boggling and is henceforth troublesome for designers. The requirement for unstructured information administration is so annoying with conventional RDBMS arrangements (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). Moreover, RDBMS turns out to be an exorbitant answer for creating light-footed web applications with direct information investigation necessities. NoSQL is developing as a proficient possibility in this situation, which connects the issues related with RDBMS innovation. The market development can credit to creative dispatches of NoSQL arrangements, and collective endeavors by NoSQL sellers and clients. The endeavors of organizations, to enhance their market offerings, are creating the request of NoSQL, as a back-end bolster (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). The emergence of agile software development is creating the demand for NoSQL (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). They offer users much more avenues to accept data in many different forms. NoSQL is adaptable as SQL but offers many more uses that can apply to many organizations.

Everyday the world progressively moves towards a digital future, and the use of physical data storage, such as files in filing cabinets, are becoming obsolete. Most companies store their information into databases to easily manage and share their data within the organization. A database management system (DBMS) is needed to to create, use and maintain databases for the efficient storage and retrieval of data.

NoSQL was created in the response to relational databases not being able to handle the scale and changing challenges of modern applications, they also cannot take advantage of the cheap, easy storage abilities and also the processing power accessible now. NoSQL includes a variety of different technologies that were developed in response to the surge of data stored by users, objects and products. They were also developed to contend with the rising frequency that the data is accessed and the performance and processing needs. [7]