SQL-an analysis

Topics: Database, SQL, Database model Pages: 5 (1258 words) Published: October 10, 2014
Database Management Systems
Database Management System is an umbrella term that refers to all sorts of completely different tools (i.e. computer programs or embedded libraries), mostly working in different and very unique ways. These applications handle, or heavily assist in handling, dealing with collections of information. Since information (or data) itself can come in various shapes and sizes, dozens of DBMS have been developed, along with tons of DB applications, since the second half of the 21st century to help in solving different programming and computerisation needs. Database management systems are based on database models: structures defined for handling the data. Each emerging DBMS, and applications created to actualise their methods, work in very different ways with regards to definitions and storage-and-retrieval operations of said information. Although there are a large number of solutions that implement different DBMs, each period in history has seen a relatively small amount of choices rapidly become extremely popular and stay in use for a longer time, with probably the most predominant choice since the past couple of decades (or even longer) being the Relational Database Management Systems (RDBMS). Database Models

Each database system implements a different database model to logically structure the data that is being managed. These models are the first step and the biggest determiner of how a database application will work and handle the information it deals with. There are quite a few different types of database models which clearly and strictly provide the means of structuring the data, with most popular probably being the Relational Model. Although the relational model and relational databases are extremely powerful and flexible - when the programmer knows how to use them, for many, there have been several issues or features that these solutions never really offered. Recently, a series of different systems and applications called NoSQL databases started to gain popularity, expeditiously, with their promise of solving these problems and offering some very interesting additional functionality. By eradicating the strictly structured data keeping style defined within the relational model, these DB systems work by offering a much more freely shaped way of working with information, thus providing a great deal of flexibility and ease -- despite the fact that they come with their own problems, some serious considering the important and indispensable nature of data. The Relational Model

Introduced in 1970s, the relational model offers a very mathematically-adapt way of structuring, keeping, and using the data. It expands the earlier designs of flat model, network model, et cetera by introducing means of relations. Relations bring the benefits of group-keeping the data as constrained collections whereby data-tables, containing the information in a structured way (e.g. a Person's name and address), relates all the input by assigning values to attributes (e.g. a Person's ID number). Thanks to decades of research and development, database systems that implement the relational model work extremely efficiently and reliably. Combined with the long experience of programmers and database administrators working with these tools, using relational database applications has become the choice of mission-critical applications which can not afford loss of any information, in any situation -- especially due to glitches or gotchas. Despite their strict nature of forming and handling data, relational databases can become extremely flexible and offer a lot, granted with a little bit of effort. The Model-less (NoSQL) Approach

The NoSQL way of structuring the data consists of getting rid of these constraints, hence liberating the means of keeping, querying, and using...
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