Database Management System: Definition, Types, and Examples

What is a DBMS?

Let's start with the definition. DBMS stands for database management system, which is typically defined as a software system that enables users to define, create, maintain, and control access to databases.

DBMS, taken together with the specialized database tools, constitutes the interface layer between the user and the data that needs to be stored, retrieved, and manipulated.

The main database models, their components, use cases, and the best-known examples of database management systems are all presented below. Whether you are a novice or a seasoned software developer, this information may come in handy.

Types of DBMS and database models

Different types of DBMS serve different purposes, quite often associated with the underlying database models. A database model is a kind of data model that determines the logical structure of a given database and the way data in this database can be stored and manipulated. Let us briefly explain the best-known types of database models.

Hierarchical model

The hierarchical data model employs the parent-child relationship mode, forming a tree-like structure, where one field contains just one value; and while parents might have multiple children, a child can have but one parent. All this makes the hierarchical model the most unsophisticated and inflexible of all.

Network model

The network model is a considerable improvement over the hierarchical model. The primary difference is that it allows more complex many-to-many relationships; that is, a child can have multiple parents. This (at least partially) solves the main problem of hierarchical databases - namely, the lack of flexibility.

Object-oriented model

An object-oriented database is defined as a collection of objects that store data along with all properties. The storage and retrieval of a complex object from an object-oriented database is absolutely transparent to the user. The majority of object-oriented databases use query languages to manage their objects.

Relational model

Finally, we have RDBMS, the most popular database model, where data is arranged and stored in tables consisting of columns and rows. Each table field represents a data value. Each row is identified with a unique key. This model is exceptionally flexible, and it uses Structured Query Language to manipulate data.

The main components of a DBMS

Now let's briefly describe various functional components that typically constitute a DBMS environment.

Storage engine

This is the core of the DBMS that is used to perform create, read, update, and delete (CRUD) operations with data.

Database access language

Also known as query language, it is used to create and manage databases and data using queries. SQL is arguably the best-known query language.

Query processor

This intermediary component helps databases interpret user queries correctly to return the required output.

Monitoring & optimization engine

This component enables DBMS to deliver performance insights and thus helps improve the performance of databases and queries.

Policies & user management

Multiple user roles are applied in order to achieve maximum flexibility and build well-defined access control.

Log manager

This is where all the logs are stored to be easily accessed at any given moment.

Reporting tools

The default reporting capabilities of these tools can be enhanced with specialized DBMS solutions.

Data utilities

These are additional utilities that help the user handle backup and restore features, data integrity checks, basic maintenance, and so on.

Three levels of architecture in DBMS

Now that we have learned about the main DBMS components, it's time to see how it all works together. Let's talk about the three levels of DBMS architecture.

Single-tier architecture

The single-tier architecture means that the database is fully available on the client machine and does not require Internet connection to manipulate databases. It's just the user and the machine.

Two-tier architecture

The two-tier architecture refers to the typical client-server architecture, where the database system is located on a server machine, and the user interacts with databases using specialized DBMS software.

Three-tier architecture

The three-tier architecture presupposes another software layer between the client and the server. The client-side DBMS software cannot communicate with the database system directly; instead, there is a server-side app acting as middleware.

DBMS users

Specialized users of database management systems can be divided into several main categories.

Software developer

Builds software products that involve databases

Database developer

Designs, implements, and manages database systems

DBA

Performs database administration
and maintenance tasks

DevOps engineer

Sets up and maintains seamless data pipelines

Data analyst

Works with data to get actionable
insights for business

Data architect

Designs and manages data systems and infrastructures

DBMS use cases in business

Now let's talk about the use of database management systems in business. These are the areas that get the biggest benefits from the application of databases in their operations.

Sector	Use
Technology	Integration of databases with commercial software products
Consulting	Provision of actionable data to facilitate data-driven decision-making in business
Telecommunication	Effective management of call records, bills, and balances
Banking	Work with customer information, accounts, payments, loans, and deposits
Manufacturing	Supply chain management with production tracking and inventory handling
Education	Management of student information, university departments, grades, courses, etc.
Finance	Storage and use of information regarding sales, stocks, and various financial tools
Sales	Work with customer, product/service, and sales information
HR management	Handling of employee information, including salaries, payrolls, paychecks, etc.
Marketing & advertising	Collection, analysis, and management of advertising data

Advantages and disadvantages of DBMS

The pros and cons of DBMS mostly depend on whether getting one for your operations is functionally and financially reasonable.

The pros:

Advanced data management capabilities
Efficiency in daily management
Integrity and security of sensitive data
Compliance with data protection standards and regulations (e.g. GDPR)
Reliable backup and recovery
Fast integration with commercial software products and streamlined development cycle

The cons:

Hardware and software costs
Possible complexity of management
Regular updates of a DBMS may require regular database maintenance
Effective work with DBMS requires professional expertise (database developers and DBAs)

The most popular DBMS in 2022

Relational databases proved to be the best choice for data storage and management in modern software products.

Currently, the most popular management systems are Microsoft SQL Server, MySQL, Oracle, and PostgreSQL.

For all of these systems, you can get solutions of different caliber that let you handle various database development and administration tasks without much effort.

SQL Server
MySQL
Oracle
PostgreSQL

SQL Server

SQL Server is arguably the world's most advanced relational DBMS, developed by Microsoft and perfectly tailored to corporate IT environments. It delivers secure and efficient data storage and an infrastructure that offers multiple auxiliary services.

MySQL

The leader among open-source solutions with ever-growing popularity. Although its core functionality is available free of charge, you can have additional paid tools provided by Oracle.

Azure SQL

Azure SQL is a highly scalable platform-as-a-service developed and delivered by Microsoft. It is based on SQL Server and allows storing relational data in the cloud.

Oracle

Oracle DBMS is noted for its complexity, difficult management, and high costs of Oracle products. However, it offers high portability and backward compatibility, easy recovery, multiple database support, and high performance.

PostgreSQL

PostgreSQL is a proven open-source DBMS that offers rich functionality, support for a variety of data types, and storage of schemaless data.

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