Let’s understand the term ‘data’ for a better understanding of databases as they are knit together closely. Data is a collection of small units of information, which are usually collected through observation. While field data is raw data collected in an uncontrolled environment, experimental data is generated within the context of a scientific investigation by observation and recording.
Referred to as the ‘oil’ of the new digital economy, data finds extensive application in a wide variety of activities such as:
Governance, and more
What is a Database?
A database is an organized collection of data that lends accessibility and manageability to data. Essentially the purpose of a database is to store, retrieve and manage data. Whether it is a telephone directory or a social media platform like Facebook – storing, managing and retrieving data is an important aspect of any database.
Types of Databases
There are several popular types of databases. Let’s discuss the commonly used databases:
As the name suggests, a centralized database stores data in a centralized location, which is accessible to users from remote locations. This is as opposed to a distributed database where data is not available in one place.
It is one of the most popular databases, stores related data, which is represented by way of tables. Each row in a table is a record, while each column holds attributes of the data. The relational model is a standard way of representing and querying data. The fact that it is intuitive as well as an efficient way to access structured information, adds to its efficacy. Its advantage also stems from the fact that it can handle business rules at a granular level.
In this database, data is stored by way of objects. Objects, in turn, have members such as fields, properties, and methods. Object databases are typically used in applications that need high performance and quick results. Some of the common applications that use object databases are telecommunications, and scientific products, molecular science, and astronomy.
A key characteristic of an open-source database is that it allows the user to create a system based on their bespoke requirements. With the deluge of data that is available, an open-source database allows the enterprise to find useful patterns. The big advantage of an open-source database is its flexibility as well as its cost-effectiveness. Some of the open-source database examples include:
Wide-column store databases, and more.
A cloud database has gained immense popularity in a jiffy. It is a database that is accessed through a cloud platform. As opposed to a traditional database, it comes with the added feature of cloud computing. The advantage is that it enables enterprise users to host databases without buying any hardware. The fact that it can be offered as a service, gives it an added impetus. It is known to support relational databases as well as NoSQL databases.
A NoSQL database essentially refers to a non-relational database. These databases store data in a format other than relational tables. NoSQL databases come in a variety of types based on their data model. Some of the types of NoSQL databases include:
They are typically used for large sets of distributed data.
These are used to store and navigate relationships. They use nodes to store data entries and edges to store relationships between entries. The use cases of graph databases include:
Essentially such databases create relationships between data and are able to query these relationships with speed.
OLTP or Online Transaction Processing is focused on maintaining data integrity in multi-access environments as well as in query processing. Essentially, it enables the real-time execution of large numbers of database transactions typically over the internet.
In the case of a personal database, data is collected and stored on personal computers. The data is generally used by a single department of an organization and is therefore accessed by a small group.
Multi-model databases refer to databases that combine different types of database models into one integrated database engine. They support multiple data models and allow users to meet different application requirements without deploying different database systems.
A JSON document database is a type of non-relational database. It is designed to store and query data as JSON documents. This is as opposed to a relational database where data is normalized across multiple tables.
What is a Database Management System (or DBMS)?
DBMS is a technology tool that supports data management. It is a package designed to define, manipulate, and manage data in a database. Some of the functions that it performs include:
Helps in creating, querying and administration of databases
It sets rules to validate data
It runs business applications
Offers data integrity and security
Examples of DBMS include Microsoft SQL Server, Microsoft Access, Oracle, SAP, and others.
Elements of database management systems
Let’s learn about the components of a database management system that are widely used:
This is the set of programs that are used to control and manage the overall database.
This consists of a set of electronic devices such as computers, I/O devices, storage devices, etc.
The main function of the DBMS is to store, process, and access data, the basic unit of information.
These are the instructions and rules that help in running the database using documented procedures
5.Database Access Language
This is used to access data from the database as well as to enter new data, update data or retrieve it.
This transforms the user queries into a series of low-level instructions.
7.Run Time Database Manager
This is the central software component of the DBMS
This is responsible for handling data in the database, and to recover the data after a failure.
It provides controlled access and rapid transaction processing
This is a reserved space within a database used to store information about the database itself.
It is a program that extracts information from one or more files and presents the information in a specified format.
With businesses having access to copious data, analysis from multiple systems is the norm. By using databases and other business intelligence tools, organizations can leverage the data to enable improved decision-making.