Discuss database management systems. Explore the multiple facets of database management systems.

Discuss database management systems. Explore the multiple facets of database management systems.

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A database management system (DBMS) is a computer program, or collection of computer programs used to collect, maintain and analyse the large volumes of data contained within vast databases such as those found among the server stacks of large multinational corporations. DBMS can seem baffling at first sight, so the guide below is designed to provide you with all the information you need to make sense of the technical terms used within the field.

Searching the databases – what is a query?

Queries are searches of the database made through the use of a query language. Query language is a simple type of programming language designed to allow direct interaction with the database by means of simple words such as ‘delete’, ‘modify’ or ‘select’. By making use of queries, the database can be accessed or modified quickly and easily without the need for third party applications. Structured Query Language (SQL) is one of the most commonly used query languages, so familiarity with SQL is advised before beginning any high-level database operations.

Evolution of Database Management System

The DBMS is perhaps most useful for providing a centralized view of data that can be accessed by multiple users, from multiple locations, in a controlled manner. A DBMS can limit what data the end user sees, as well as how that end user can view the data, providing many views of a single database schema. End users and software programs are free from having to understand where the data is physically located or on what type of storage media it resides because the DBMS handles all requests.

The DBMS can offer both logical and physical data independence. That means it can protect users and applications from needing to know where data is stored or having to be concerned about changes to the physical structure of data (storage and hardware). As long as programs use the application programming interface (API) for the database that is provided by the DBMS, developers won’t have to modify programs just because changes have been made to the database.

With relational DBMSs (RDBMSs), this API is SQL, a standard programming language for defining, protecting and accessing data in a RDBMS.

Types of Database:

Flat File Database – This is probably the easiest to understand but at present rarely used. You can think of this as a single huge table. Such types of datasets were used long back in 1990s, when data was only used to retrieve information in case of concerns. Very primitive analytics were possible on these database.

Relational Database – Soon people starting realizing that such tables will be almost impossible to store on a longer run. The Flat File brought in a lot of redundant data at every entry. For instance, if I want to make a single data-set with all products purchased at a grocery store with all information of the customer and product, we will have every single row consisting of all customer and product information. Wherever we have a repeat product or customer, we have repeat data.

People thought of storing this as different tables and define a hierarchy to access all the data, which will be called as hierarchical database.

Hierarchical databases – are those which are organised as the branches of a tree, with the root directory at the top, followed by parent and child directories of various classifications. These databases are incredibly easy to update since the directory trees are already defined and additions can be made by simply adding branches.

Object-orientated databases – are designed to handle objects rather than discrete columns of data sorted into fields. The object-orientated database is a powerful way to organise multimedia files, but is also more expensive to implement, and requires more work to maintain and catalogue data.

Network databases – are quite similar to hierarchical databases, except that each child (referred to as a member) can have more than one parent (referred to as an owner), thereby allowing the database to appear as more of a network or web of related data rather than a tree.

Relational databases – allow users to access data using a common field, such as a username, identification number or product code, rather than passing through a hierarchy to access the required information.

It is very similar to your folder structure on the laptop. Every folder can contain sub-folder and each sub-folder can still hold more sub-folders. Finally in some folders we will store files. However, every child node (sub-folder) will have a single parent (folder or sub-folder). Finally, we can create a hierarchy of the dataset:

Hierarchical databases, however can solve many purposes, its applications are restricted to one-to-one mapping data structures. For example, it will work well if you are using this data structure to show job profile hierarchy in a corporate. But the structure will fail if the reporting becomes slightly more complicated and a single employee reports to many managers. Hence, people thought of database structures which can have different kinds of relations. This type of structure should allow one-to-many mapping. Such table came to be known as Relational database management system (RDBMS). Following is an example RDBMS data structure:

As you see from the above diagram, there are multiple keys which can help us merge different data sets in this data base. This kind of data storage optimizes disc space occupied without compromising on data details. This is the data base which is generally used by the analytics industry. However, when the data looses a structure, such data base will be of no help.

NoSQL Database – NoSQL is often known as “Not Only SQL”. When people realized that unstructured text carry tonnes of information which they are unable to mine using RDBMS, they started exploring ways to store such datasets. Anything which is not RDBMS today is loosely known as NoSQL. After social networks gained importance in the market, such database became common in the industry.

Following is an example where it will become very difficult to store the data on RDBMS;

Facebook stores terabytes of additional data every day. Let’s try to imagine the structure in which this data can be structured:

In the above diagram, same color box fall into same category object. For example the user, user’s friends, who liked and Author of comments all are FB users. Now if we try to store the entire data in RDBMS, for executing a single query which can be just a response of opening home page, we need to join multiple tables with trillions of row together to find a combined table and then run algorithms to find the most relevant information for the user. This does not look to be a seconds job for sure. Hence we need to move from tabular understanding of data to a more flow (graph) based data structure. This is what brought NoSQL structures. We will discuss NoSQL databases in our next article. We will also compare various types of NoSQL databases to understand the fitment of these databases.

Components of DBMS

DBMS have several components, each performing very significant tasks in the database management system environment. Below is a list of components within the database and its environment.

Software: This is the set of programs used to control and manage the overall database. This includes the DBMS software itself, the Operating System, the network software being used to share the data among users, and the application programs used to access data in the DBMS.

Hardware: Consists of a set of physical electronic devices such as computers, I/O devices, storage devices, etc., this provides the interface between computers and the real world systems.

Data: DBMS exists to collect, store, process and access data, the most important component. The database contains both the actual or operational data and the metadata.

Procedures: These are the instructions and rules that assist on how to use the DBMS, and in designing and running the database, using documented procedures, to guide the users that operate and manage it.

Database Access Language: This is used to access the data to and from the database, to enter new data, update existing data, or retrieve required data from databases. The user writes a set of appropriate commands in a database access language, submits these to the DBMS, which then processes the data and generates and displays a set of results into a user readable form.

Query Processor: This transforms the user queries into a series of low level instructions. This reads the online user’s query and translates it into an efficient series of operations in a form capable of being sent to the run time data manager for execution.

Run Time Database Manager: Sometimes referred to as the database control system, this is the central software component of the DBMS that interfaces with user-submitted application programs and queries, and handles database access at run time. Its function is to convert operations in user’s queries. It provides control to maintain the consistency, integrity and security of the data.

Data Manager: Also called the cache manger, this is responsible for handling of data in the database, providing a recovery to the system that allows it to recover the data after a failure.

Database Engine: The core service for storing, processing, and securing data, this provides controlled access and rapid transaction processing to address the requirements of the most demanding data consuming applications. It is often used to create relational databases for online transaction processing or online analytical processing data.

Data Dictionary: This is a reserved space within a database used to store information about the database itself. A data dictionary is a set of read-only table and views, containing the different information about the data used in the enterprise to ensure that database representation of the data follow one standard as defined in the dictionary.

Report Writer: Also referred to as the report generator, it is a program that extracts information from one or more files and presents the information in a specified format. Most report writers allow the user to select records that meet certain conditions and to display selected fields in rows and columns, or also format the data into different charts.

Advantages of a DBMS

The main benefit of a well-designed DBMS is its ability to bridge the gap between the database itself and users of differing skill levels. Opening up the database to all of your workers is a great way to boost productivity and efficiency, while still keeping tight controls on the data your system is able to store. Although access to a database is generally in the form of an ‘all or nothing’ event, passwords can be installed in order to facilitate the access of only certain users to the database, thereby maximising the security of your records.

Disadvantages of a DBMS

The main disadvantage of a DBMS is its cost; these systems are hugely expensive for a large company which requires a license to facilitate use of the program on a large number of computers. Despite this, the majority of users will attest that the ease and speed of database searches and maintenance that these systems are able to provide vastly outweighs any cost incurred during installation. One additional problem associated with a DBMS is its security. Since access to the database is ‘all or nothing’, if someone is able to gain unauthorised access to any part of the database, they will have free roam of the entirety of its contents. For this reason, powerful security features must be put in place to prevent unauthorised users from making use of the database without the appropriate permissions, and sensitive documentation should perhaps be stored on a separate database or in encrypted, password protected files.

Ref:

Components of a Database Management System

http://www.opendatabasealliance.com/dbms.htm

Types of database management system and their evolution

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