What is a database?

A collection of structured information in an organized way, stored electronically in a computer system, is called a database.

Such structured information or data in electronic form is controlled and managed by a DBMS which expands to become a database management system. Both data and the DBMS combined along with their applications are called database systems.

The structured information is usually stored in rows and columns in tabular forms so as to make data processing simpler and more efficient.

SQL (Structured Query Language) is the most common language to be used to write data. The data in a database can be easily altered, accessed, controlled, updated, and managed in an organized way.

History and Evolution

The first file-based databases were introduced in 1968 wherein the data was stored in flat files. They required extensive programming in any of the third-generation languages.

From 1968 to 1980, Hierarchical Databases became popular. Also, network data model databases were standardized in 1971. From 1971, the era of relational databases began which prevails till the present.

The most recently developed databases are cloud databases which offer added advantages like lower costs, full automation, and increased accessibility.

Difference between a Spreadsheet and Database

Types of Databases

• Non-relational databases – Also known as NoSQL. These can contain both unstructured and semi-structured data which can be accessed, stored, and even modified. These types of databases have recently become very famous due to the increasing complexity of web applications.
  
  
• Relational databases – These contain structured information in the forms of tables which contain rows and columns. These are the most efficient and flexible types of databases to access the data.
  
  
• Cloud database – A database that is stored in a private, public, or hybrid cloud computing platform, it is known as a cloud database. It may contain any structured or unstructured information and the maintenance tasks on that information are carried out by a service provider. Examples of cloud database models include DBaaS.
  
  
• When the source code of a database system is open source, such a database is known as an open-source database system. It could be either a relational or non-relational database.
  
  
• The kind of database that amalgamates various kinds of database models into a single integrated backend, is called a multi-model database. These kinds of databases can accommodate different types of data.
  
  
• Autonomous databases or self-driving databases are the most recently developed databases that are cloud-based and operate on machine learning. The database tuning, security, backup, update, everything is done automatically. Just the regular managerial tasks on the data are performed by data administrators.
  
  
• The databases that store data in JSON format instead of tables or rows and columns are called JSON databases or document databases.
  
  

Usage

More than a hundred industries of the world currently use big data and hence databases. Digital filmmaking, satellite imaging, healthcare industries, education industries, e-commerce industries, Telecommunication, tourism, marketing, mobile applications, financial industries, are just a few examples of industries that need effective databases to effectively manage and utilize their data to grab their potential opportunities.

Database Software

The software that helps in easing out the process of file creation, recording, data entry, data updation, reporting, data editing are called database software. Such a software is also responsible for creation, editing and maintenance of database files along with its records.

Data management can be made more efficient and simpler by using database software. The interface of database software is usually graphical so as to easily manage existing data and create new data.

Challenges

• The enormous increase in data volume – One of the primary challenges in databases these days is the magnificent increase in data volume. Even the word explosion would be less to give an idea about the humongous data that is being added every day.
  
  Data is coming in from everywhere, from sensors, from machines, from more than 10 of other sources that makes it very hard for database administrators and managers to manage and organize the same in efficient ways.
  
  
• Data Security – With the increase in volume also comes the increased risk. This is why ensuring the security and safety of the data is an even bigger challenge. Data breaches, data hacking, data phishing, and other cybercrimes are becoming very common.
  
  Data can also not be kept secret because it has to be accessed by various users. So, making the data accessible and secure at the same time is a crucial responsibility.
  
  
• Real-time access – The pace of the creation of new data is so fast that companies demand real-time access to their data to support decision-making at the right time to take advantage of the upcoming opportunities.
  
  So, the databases need to be evolved in accordance with the pace of the world. 
  
  
• Infrastructure – Technology changes with the blink of an eye so real-time upgrades are required for maintaining and managing the database and its infrastructure. When volumes grow, the databases become even more complicated to manage so the companies are forced to hire a competent workforce to supervise and upgrade their databases accordingly.
  
  

Future scope and Conclusion

Consolidation around big data holds enormous future scope for databases to make data readily available to provide efficient data-driven services and analytics. The fact that 4.4 zettabytes of data in the world in 2015 have increased to 44 zettabytes in 2020 itself defined the enormous increase in the amount of data volume.

No industry is going to be left untouched from the use of big data in the near future and so the need for databases is going to keep growing with huge volumes. With increased demand, fast-paced evolution and upgrades will go hand in hand.