Basics of Database Management System


The Basics of Database Management System is an introductory guide to database management systems and database design. The book covers the history and types of database management systems, the structure of a database, data modeling and normalization, and SQL basics. It also covers advanced SQL techniques, database design and administration, and the use of NoSQL databases for big data processing.


The main objectives of the book are to provide readers with a solid understanding of:

  • The definition and functions of a database management system
  • The structure and organization of a database
  • Data modeling and normalization techniques
  • The basics of SQL and how to use it to manipulate and query a database
  • Advanced SQL techniques for data analysis and management
  • The principles of database design and administration
  • The role of NoSQL databases in the big data processing

Definition of a database and database management system

A database is a collection of data that is organized in a specific way so that it can be easily accessed, updated, and managed. A database management system (DBMS) is a software program that enables users to create, modify, and manage databases.

History of database management systems

The history of database management systems dates back to the 1960s when the first database management systems were developed. These early systems were designed to handle the large amounts of data that were being generated by businesses and other organizations. Over time, the capabilities of database management systems have evolved, and they are now used in a wide variety of applications, including financial management, inventory control, and customer relationship management.

Characteristics of DBMS

Some characteristics of a database management system (DBMS) include:

  1. Data storage and organization: A DBMS stores data in a structured format, such as tables with rows and columns, and provides tools for organizing and accessing the data.
  2. Data integrity and security: A DBMS ensures the integrity of the data by enforcing rules and constraints, and it provides security measures to protect the data from unauthorized access.
  3. Data manipulation: A DBMS provides tools for adding, modifying, and deleting data, as well as for querying the data.
  4. Concurrency control: A DBMS handles multiple users accessing and modifying the data simultaneously, ensuring that the data remains consistent and that users do not overwrite each other's changes.
  5. Data recovery: A DBMS includes features for backing up and restoring data in case of data loss or corruption.

Examples of DBMS

Examples of DBMS include:

  • MySQL
  • Oracle
  • Microsoft SQL Server
  • PostgreSQL
  • MongoDB
  • Cassandra
  • Redis
  • SQLite

Types of database management systems

There are several types of database management systems, including:

  1. Relational database management systems (RDBMS): These systems store data in the form of tables, with rows representing individual records and columns representing the attributes of each record.
  2. Object-oriented database management systems (OODBMS): These systems store data in the form of objects, which are structured data elements that contain both data and behavior.
  3. NoSQL database management systems: These systems do not use the traditional SQL language used by RDBMSs, and they are designed to handle large amounts of data that are distributed across multiple servers.
  4. In-memory database management systems: These systems store data in the main memory of a computer, rather than on a disk, which makes them faster than traditional database management systems.

Hierarchical databases and Network databases are also types of database models.

The Structure of a Database

Tables and columns

In a database, data is usually organized into tables, with each table containing one or more rows (also known as records) and columns (also known as fields). Each row in a table represents a unique entity, and each column represents an attribute of that entity.

For example, in a table of employees, each row might represent a single employee, and each column might represent an attribute such as the employee's name, salary, or department.

Primary and foreign keys

A primary key is a column (or combination of columns) in a table that uniquely identifies each row in the table. A foreign key is a column (or combination of columns) in a table that refers to the primary key of another table. Foreign keys are used to establish relationships between tables.

For example, in a database of employees and departments, the "DepartmentID" column in the employee's table might be a foreign key that refers to the primary key of the department's table.

Data types and constraints

Data types are used to specify the type of data that can be stored in a column. Constraints are used to specify rules that data must follow when it is entered into a table.

For example, a column in a table might be defined as an integer data type with a constraint that requires the value to be greater than zero. Alternatively, a column might be defined as a text data type with a constraint that requires the value to be unique across all rows in the table.

Data Modelling and Normalization

Entity-relationship diagrams

An entity-relationship (ER) diagram is a graphical representation of the relationships between entities in a database. Entities are represented by boxes, and relationships between entities are represented by lines connecting the boxes. ER diagrams are used to model and design databases, and they can help users understand the structure and constraints of a database.

For example, an ER diagram for a database of employees and departments might include boxes for the entities "Employee" and "Department," and a line connecting the two entities to represent the relationship "works in."

First, second, and third normal forms

Normalization is the process of organizing a database in a way that minimizes redundancy and dependency. There are several levels of normalization, known as normal forms, which are used to ensure that a database is structured in an efficient and logical way.

The first normal form (1NF) requires that all columns in a table contain atomic values (values that cannot be further divided). The second normal form (2NF) requires that all non-key columns in a table be dependent on the primary key. The third normal form (3NF) requires that all non-key columns in a table be directly dependent on the primary key.

For example, consider a table of employees that includes columns for "Name," "Department," and "Manager." In 1NF, the "Name" column would contain a single value (e.g. "John Smith") rather than a list of values (e.g. "John," "Smith"). In 2NF, the "Department" column would be dependent on the primary key (e.g. "EmployeeID") rather than on the "Name" column. In 3NF, the "Manager" column would be directly dependent on the primary key, rather than on the "Department" column.

SQL Basics

SQL stands for Structured Querry Language. Below are the basics of SQL.

Select Statements

The SELECT statement is used to retrieve data from a database. It allows you to specify the columns you want to include in the result set, as well as any conditions that must be met in order for a row to be included.


SELECT * FROM users;

SELECT first_name, last_name, email FROM users WHERE city='New York';

SELECT COUNT(*) FROM users WHERE signup_date > '2022-01-01';

Insert, Update, and Delete Statements

The INSERT statement is used to add new rows to a table. The UPDATE statement is used to modify existing rows in a table. The DELETE statement is used to remove rows from a table.


INSERT INTO users (first_name, last_name, email) VALUES ('John', 'Doe', '');

UPDATE users SET city='San Francisco' WHERE user_id=123;

DELETE FROM users WHERE signup_date < '2020-01-01';

Joins and Subqueries

JOIN clauses are used to combine rows from two or more tables based on a related column. There are several different types of JOINs, including INNER JOIN, OUTER JOIN, and CROSS JOIN.

A subquery is a SELECT statement that is nested within another SELECT, INSERT, UPDATE, or DELETE statement. It is used to return data that will be used in the outer query.


SELECT u.first_name, u.last_name, o.order_total

FROM users u

INNER JOIN orders o ON u.user_id = o.user_id;

SELECT * FROM users WHERE user_id IN (SELECT user_id FROM orders WHERE order_total > 100);

Advanced SQL Techniques

Group By, Having, and Aggregate Functions

The GROUP BY clause is used to group rows with similar values together, and is often used in conjunction with aggregate functions such as SUM, AVG, and COUNT. The HAVING clause is used to filter the groups based on a specified condition.


SELECT city, COUNT(*) as num_users

FROM users

GROUP BY city;

SELECT city, SUM(order_total) as total_sales

FROM orders


HAVING total_sales > 1000;

Stored Procedures and Triggers

A stored procedure is a pre-defined set of SQL statements that can be called by name. It is used to perform a specific task, such as retrieving data or updating a table. A trigger is a set of SQL statements that are automatically executed when a specific event occurs, such as the insertion of a row into a table.


CREATE PROCEDURE get_user_orders (IN user_id INT)


  SELECT * FROM orders WHERE user_id = user_id;


CREATE TRIGGER update_order_total

AFTER INSERT ON order_items



  UPDATE orders SET order_total = (SELECT SUM(price) FROM order_items WHERE order_id = NEW.order_id) WHERE order_id = NEW.order_id;


Views and Indexes

A view is a virtual table that is created based on a SELECT statement. It does not store any data itself, but rather displays data from one or more underlying tables. An index is a data structure that is used to improve the performance of certain types of queries.


CREATE VIEW active_users AS

SELECT * FROM users WHERE last_login_date > '2022-01-01';

CREATE INDEX index_name ON table_name (column_name);

Database Design and Administration

Designing a Database for Performance and Scalability

Proper database design is essential for ensuring that a database performs well and can scale as the size of the data increases. This includes choosing the right data types and structures, normalizing the data to minimize redundancy, and using indexes to speed up queries.



  user_id INT PRIMARY KEY,

  first_name VARCHAR(50) NOT NULL,

  last_name VARCHAR(50) NOT NULL,


  password CHAR(60) NOT NULL,

  city VARCHAR(50) NOT NULL,

  signup_date DATE NOT NULL



  order_id INT PRIMARY KEY,

  user_id INT NOT NULL,

  order_date DATE NOT NULL,

  order_total DECIMAL(10,2) NOT NULL,

  FOREIGN KEY (user_id) REFERENCES users(user_id)


CREATE INDEX index_name ON orders (order_date);

Backups and Recovery

Creating regular backups of a database is essential for data protection and recovery in the event of data loss or corruption. There are several different methods for backing up a database, including using native utilities provided by the database management system and using third-party tools.


mysqldump -u username -p db_name > backup.sql

pg_dump -U username -d db_name > backup.sql

Security and Permissions

Ensuring the security of a database is critical for protecting sensitive data and preventing unauthorized access. This includes setting up proper authentication and authorization mechanisms, as well as implementing measures such as encryption and firewall protection.


GRANT SELECT, INSERT, UPDATE, DELETE ON table_name TO 'username'@'localhost';

REVOKE ALL PRIVILEGES ON table_name FROM 'username'@'localhost';

CREATE USER 'username'@'localhost' IDENTIFIED BY 'password';

DROP USER 'username'@'localhost';

NoSQL and Big Data

Introduction to NoSQL Databases

NoSQL, or "Not Only SQL," is a class of databases that are designed to handle large amounts of data that is not well-suited to the relational model. These databases are often used in scenarios where the data is highly distributed, has a high volume of reads and writes, or has a complex structure that is difficult to model in a traditional relational database.

Examples of NoSQL databases include MongoDB, Cassandra, and Redis.


# Inserting a document into a MongoDB collection


  first_name: "John",

  last_name: "Doe",

  email: "",

  signup_date: ISODate("2022-01-01")


# Updating a value in a Redis hash

HMSET user:123 first_name "John" last_name "Doe" email ""

Distributed Systems and Big Data Processing

In a distributed system, a database or application is spread across multiple machines in order to scale horizontally and handle a large volume of data. This is often necessary for processing "big data," which refers to data sets that are too large or complex to be processed using traditional databases or data processing tools.

Examples of distributed systems and big data processing tools include Hadoop and Spark.


# Running a MapReduce job on a Hadoop cluster

hadoop jar hadoop-streaming.jar \

  -input input_dir \

  -output output_dir \

  -mapper \


# Counting the number of words in a text file using Spark

val textFile = sc.textFile("hdfs:///input_dir/*.txt")

val counts = textFile.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_ + _)


In Conclusion

At the conclusion of the book, the key concepts covered in the book will be summarized and the future trends in database management will be discussed. The book will conclude with a discussion of the importance of database management systems in modern society and the various career opportunities available in the field.


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