Database Management System (DBMS)

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Database Management System (DBMS)

Database Management System (DBMS)

What does a database management system (DBMS) mean?

The database management system (DBMS) is a software package designed to define, manipulate, retrieve, and manage data in a database. DBMS usually manipulate the data itself, data format, field name, record structure, and file structure. It also defines rules for validating and manipulating these data.

The database management system is built around specific data management concepts because the practice of managing databases continues to evolve. Older databases only deal with individual data in a special format. Today’s more evolved systems can handle different types of data in fewer formats and combine them in more complex ways.


A database management system is a collection of interconnected data and a set of programs that allow you to access that data.

A database is a collection of information. The primary objective of DBMS is to provide an easy and efficient method of storing and retrieving database information.

DBMS allows us to create a structure for storing information as well as a technique for manipulating that information. DBMS also ensures the security of the data saved, even if the system fails or unauthorized access attempts are made.

The following are the limitations of the data processing environment:

1) Data redundancy and consistency: Different files include programs developed in different programming languages by different users in different formats. As a result, the same information may appear in many files. It might result in data inconsistencies.
If a customer’s address changes, it may be recorded in one copy of the data but not in the other.

2) Difficulty accessing data: The file system environment does not allow for the retrieval of essential data in a convenient and efficient manner.

3) Data isolation: Because data is distributed over several files, it must be separated because the files may be in different formats.

4) Data integrity issues: Data values recorded in a database must adhere to consistency requirements. When restrictions contain several data items from separate files, a problem arises.

5) Atomicity issues: If a failure occurs, data must be stored in the constant state that existed before to the event. For example, if a person abc is transferring Rs 5000 from his bank account to the account of pqr, and abc has withdrawn the money but before it is transferred to pqr’s account, a system failure happens, then Rs5000 should be put back into abc’s bank account.

6) Anomalies in concurrent access: Many systems allow numerous users to change data at the same time. Concurrent changes should not lead to inconsistency.

7) Security issues: Not all user of the database system should have access to all data. Unauthorized users should not have access to the database.

Database Management System (DBMS)

The database management system model has changed a lot over time. This is a key part of understanding how the various DBMS options work.

The first type of database management system is mainly composed of a hierarchical structure and a network model.

  • A hierarchical model is a model in which each node or component has a child / parent relationship with another node or component.
  • In the network model, the difference is that a single component can have multiple relationships; think of it as a single node that can be “multicast” connected.

However, over time, these models were replaced by something called relational databases. In the relational database model, each component has attributes linked to its identity through the layout of the database table. The rows and columns of a single database table include these identities and attributes in such a way that SQL or traditional structured query language can be used to extract diverse information about these relational models.

Topics Covered:

1.1 Database management system
1.2 Data Independence
1.3 Data Abstraction
1.4 Data Models
1.5 DBMS Architecture
1.6 Users of DBMS
1.7 Overview of Conventional Data Models

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