First defined in the year 1970 by Edgar Codd of IBM’s San Jose Research Laboratory, rational database is a database that has a collection of tables of data items. Initially, they were designated and systematized according to the relational model. In other words, relational database represents the database management system (DBMS). It was initially introduced by E. Codd, and it has turned to be a predominant choice for the storage of information for instance in the financial records, manufacturing, personal data, and logistical information (Whitehorn & Marklyn, 2007). It is on record to have substituted the legendary hierarchical databases and the network databases since they were easier to use and to understand. Even so, the rational database is with a contest especially from the object database that were developed with the aim of making an attempt of solving the object-relational impedance mismatch that exists in relational database and the XML databases. In the relational database model, each table schema must identify a column or group of columns that are termed as primary key whose main purpose is to distinctively categorize each row (Halpin & Morgan, 2008). As a result, the relationship would be formulated between each row in the table and columns in another table. That was by coming up with a foreign key whose main purpose was to indicate the primary key of another table.
There are various reasons that would be tabled indicating why relational databases are necessary. For instance, relational databases are required since they allow for a swift comparison of information. That is made possible by the manner in which data were arranged in columns. In addition, they are necessary because it adopts a uniformity to build completely new tables out of the required information from the already existing tables (Whitehorn & Marklyn, 2007). That is to mean that, the relational databases take the advantage of the correspondence of data to increase the speed and flexibility of the database.
The relational database encompasses a process called normalization. It is a process that is defined as the procedure for proficiently consolidating information in a database. It does include a set of measures and actions that are categorically intended to eliminate non-simple domains also termed as non-atomic values, as well as the exclusion of redundancy of data. As a result, data manipulation irregularities and loss of data veracity would be barred and avoided (Satzinger, Jackson, & Burd, 2008). Equally, the normalization process is aimed at reducing the space that a database would use or consume resulting in logically stored information. That explains why database normalization would essentially were termed as the process of heightening the table structures of a database. The normal forms, also developed by Codd as an imperative part of the relational database model has turned out to be the most collective form of normalization that is applied to databases (Satzinger, Jackson, & Burd, 2008). The process of normalization, therefore, is imperative because it enables the thorough investigation of the numerous fragments or sections of data that end up stored within the database. More specifically, normalization plays a crucial role in the determination on how the information would end up interrelated while they were stored in a relational database. As a result, the process of information retrieval is assured to result to a success something that reduces the possibilities of de-normalized database tables (Satzinger, Jackson, & Burd, 2008). The de-normalized databases are designated as flattened database something that has the capabilities of reducing performance of the relational database, but once adopted; it facilitates the exhaustive and comprehensive exploration of the various departments of data that are stored inside the database system.
Coupled with the exceeding elaborations, the deliverables in both the logical and physical models indicates their differences. For instance, the characteristic deliverables of the physical model include the server classical illustrations that portrays the tables, columns, and the connections that exists within the database, and the user opinion or feedback documentation that is also known as the database design documentation. On the contrary, the logical deliverables includes but not limited to the entity relationship diagrams that are also called an analysis ERD. They are meant to offer the users with a depiction of the various sections of information for the business in which the model would be applied. In addition, the logical model has the business process illustrations that are meant to indicate all the parent and child progressions that are undertaken by the users or an organization where the model is applied. In general, appreciative of the dissimilarities as well as the similarities of the physical and logical database design models would enable an individual formulate a enhanced, systematized, and effective database system that will bring out better outcomes.
It is worth noting that the relational database is not only a graphical representation, but also, it is a full language on how to communicate the structure. That is bearing in mind that a model is usually associated with pictures. The logical and physical models are two forms that are important in the creation of a relational database. They are both necessary in the process of viewing present database formulated for a certain purpose (Davidson & Moss, 2012). Likewise, they are both used to indicate the precise and comprehensive connection of business requirements of the database. While the logical model originates first and signifies the implementation of non-specific data, the physical model denotes the implementation of precise details applied in the database. Distinctively, logical model is extremely structured on what the database is endeavoring to accomplish for the customer with the goal remaining to get the necessary information from the user so that the problem were attained (Davidson & Moss, 2012). In addition, some constructs do occur in the logical model unlike in the physical model in a style that cannot be implemented directly or in a relational database. Alternatively, the physical model has two sections. The first one is the RDBS. It is a specific model that enables the implementation of logical model without the elimination of the intended meaning. An additional section of the physical model is an adaptation of implementation to a combination of users as well as the hardware (Domanski, 2000). For instance, the DBA has the possibility of changing or even moving the database to a new server in the process of production. However, the general format of a physical model depends on the software that already exists within an organization. That implies that the model will be applied to the physical database because it is software specific, unlike the logical database that is dependent on the necessities of the business that it would be applied to.
Structured Query Language denoted as SQL has its origin in the 1970s thanks to the IBM laboratories where it was first developed and initially was known as the SEQUEL. Bearing in mind that the spread of websites on the World Wide Web makes the process cumbersome and complicated, the SQL did turn to be imperative (Leondes, 2002). That is as a result of the fact that the complicated processes were rationalized by the SQL programming language. Importantly, that reveals the reasons why the SQL language has over the years were termed as a user friendly language. Since it allows the querying and editing of information that stored in a certain database management system, it indicates how it enables the simplified interactions with the users (Davidson & Moss, 2012). Initially, the access to stored information would require a DBMS programmer to write software codes that would enable the user to effectively access the information and that would be something that would be a time consuming as well as tiresome. Hence, the development of SQL as a user friendly language solved the hectic needs of the users as a single command would result to better interactions with the user. Moreover, the enhanced speed of the language enabled large retrievals of information something that would be done at a faster rate unlike before (Leondes, 2002). Worth noting also is the fact that the SQL did not necessitates the user to have specific codes to access the information, hence, qualifying the language as a user friendly language.
Davidson, L., & Moss, J. (2012). Pro SQL server 2012 relational database design and implementation. New York: Apress.
Domanski, P. (2000). Practical guide to relational database design: From business analysis via data modelling to. S.l.: Domanski-Irvine Book Comp.
Halpin, T. A., & Morgan, A. J. (2008). Information modeling and relational databases. Burlington, MA: Elsevier/Morgan Kaufman Publishers.
Leondes, C. T. (2002). Database and data communication network systems: Techniques and applications. Amsterdam: Academic Press.
Satzinger, J. W., Jackson, R. B., & Burd, S. D. (2008). Systems analysis and design in a changing world. Cambridge Mass: Course Technology.
Whitehorn, M., & Marklyn, B. (2007). Inside relational databases with examples in Access. London: Springer.