What is RDBMS, Brief History of RDBMS, How RDBMS works?


RDBMS (Relational Database Management System) is a software system used to manage relational databases. In this tutorial, we will learn about what RDBMS is, how it works, and a brief history of RDBMS.

What is RDBMS?

An RDBMS is a type of DBMS (Database Management System) that manages data in the form of tables with columns and rows. It stores data in a structured format and enforces data integrity by using relationships between tables. An RDBMS also provides a set of tools to create, update, and query the database.

The main components of an RDBMS are:

  • Tables: RDBMS stores data in tables, which are made up of columns and rows.
  • Columns: Each column contains data of a specific type, such as a text, number, or date.
  • Rows: Each row represents a single record or instance of data in the table.
  • Relationships: RDBMS uses relationships between tables to maintain data integrity and enforce business rules.

Some popular examples of RDBMS include Oracle, MySQL, Microsoft SQL Server, PostgreSQL, and SQLite.

Brief History of RDBMS

RDBMS has its roots in the mathematical concept of set theory and relational algebra. In the early 1970s, E.F. Codd, a computer scientist at IBM, introduced the concept of a relational model for data management. He proposed a language called SQL to interact with the database.

In 1979, the first commercially available RDBMS, Oracle, was released by Relational Software Inc. (later renamed to Oracle Corporation). Other RDBMSs followed, including IBM’s DB2 and Microsoft’s SQL Server.

Since then, RDBMS has become the dominant type of database management system in use today, powering many of the world’s largest applications and websites.

How RDBMS works?

RDBMS works by storing data in tables that have a predefined structure, called a schema. The schema defines the columns, data types, and relationships between tables. Data is stored in the tables in a standardized format, which makes it easier to search, sort, and manipulate.

RDBMS uses SQL (Structured Query Language) to manage and manipulate data. SQL is a programming language used to create, update, and query databases. SQL allows you to create tables, insert data, update records, and retrieve data from the database.

RDBMS provides several key features that make it easy to manage and maintain data, such as:

  • Data Integrity: RDBMS enforces data integrity by using constraints, such as primary keys and foreign keys, to ensure that data is accurate and consistent.
  • Scalability: RDBMS can scale up or down to handle large amounts of data and can support multiple users and applications accessing the database simultaneously.
  • Security: RDBMS provides security features, such as user authentication and access control, to protect the database from unauthorized access.
  • Transactions: RDBMS allows transactions, which are a series of database operations, to be performed atomically. This means that all operations within a transaction are either completed or none of them are completed.

Here are some common terminologies used in RDBMS:

Tables: Tables are the most basic component of an RDBMS. They are used to store data in a structured manner. A table is a collection of rows and columns, where each row represents a record and each column represents a field of data. Tables can be related to other tables through primary and foreign keys.

In a relational database management system (RDBMS), a table or relation is a collection of related data organized in a structured format. A table consists of rows and columns, where each row represents a single record, and each column represents a specific piece of information or attribute about the record.

For example, a table called “Customers” may contain columns such as “Customer ID,” “Name,” “Address,” “Phone Number,” and “Email.” Each row in the table represents a specific customer, with each column providing a piece of information about that customer.

Tables are the fundamental building blocks of a relational database, and they allow data to be organized and stored in a logical and efficient manner. They also enable data to be easily retrieved, searched, and manipulated using SQL (Structured Query Language) commands.

An example of a table (also known as relation) in a RDBMS could be a table called “Customers” that stores information about customers of a company. This table could have columns such as “CustomerID”, “FirstName”, “LastName”, “Email”, “Phone”, “Address”, and “City”.

Here is an example of how the table could look like with sample data:

table example in rdbms

In this example, the table “Customers” has columns for customer information such as their ID, name, email, phone number, address, and city. Each row in the table represents a different customer, and the data in each cell corresponds to a specific attribute of that customer. This information could be used for various purposes such as analyzing customer demographics, sending targeted marketing emails, or tracking sales by location.

Rows: A row, also known as a record, is a single instance of data within a table. Each row in a table represents a unique record, and each column within the row represents a field of data for that record.A row, also known as a record or tuple, is a collection of related data in a database table. Each row represents a single instance of an entity or object, such as a customer, order, or employee, and contains specific information about that entity.For example, in a customer table, each row would represent a single customer and contain attributes such as the customer’s name, address, phone number, and email. The values in each column of the row describe specific characteristics of that customer.

Rows are important because they allow users to store and organize data in a structured and meaningful way, making it easier to search, filter, and analyze information.

Columns: A column, also known as a field, is a single unit of data within a table. Each column within a table represents a specific type of data, such as a name, address, or date.In a relational database, a column is also known as an attribute. It represents a specific type of data that can be stored in the database table. Each column has a name and a data type that defines the type of data that can be stored in that column.For example, in a table that stores employee data, there may be columns for employee ID, first name, last name, email address, and salary. Each of these columns represents a different attribute of the employee data, with a specific data type that describes the type of information that can be stored in that column.

Columns can also have other properties such as constraints, which limit the type of data that can be stored in the column, and default values, which specify a value that should be used if no value is provided for that column.

Degree: Degree in a relational database refers to the number of attributes or columns in a table. It is also known as the cardinality or arity of a table. The degree of a table is fixed at the time of its creation and remains the same throughout the life of the table. It is an important aspect of the table’s design and determines the number and type of values that can be stored in the table. For example, if a table has a degree of 5, it means that there are 5 attributes or columns in the table.

Also Read:  Database Languages in DBMS

Cardinality: Cardinality in a relational database refers to the number of instances of one entity that can be associated with another entity. In other words, it defines the relationship between two tables in terms of the number of records that can be associated with each other.There are three types of cardinality in a relational database:

    1. One-to-One (1:1) Cardinality: In a one-to-one relationship, each record in the first table is related to only one record in the second table, and vice versa. For example, a person may have only one passport, and a passport can only be issued to one person.
    2. One-to-Many (1:N) Cardinality: In a one-to-many relationship, each record in the first table can be related to many records in the second table, but each record in the second table can only be related to one record in the first table. For example, a customer can place many orders, but each order is placed by only one customer.
    3. Many-to-Many (N:M) Cardinality: In a many-to-many relationship, each record in the first table can be related to many records in the second table, and vice versa. For example, a student can enroll in many courses, and each course can have many students. To represent a many-to-many relationship in a relational database, a third table called a junction table or bridge table is used to store the relationship between the two tables.

Domain: In a relational database, a domain refers to the set of possible values for a given attribute. It defines the data type, format, and constraints that can be applied to the values stored in a particular column of a table.

For example, a domain for the “Age” attribute of a “Person” table could be defined as a positive integer between 1 and 120. This would restrict the values stored in the “Age” column to be only whole numbers between 1 and 120, and any attempt to enter a value outside this range would be rejected by the database.

Domains help to ensure data integrity and consistency by enforcing rules for the types of values that can be stored in each column of a table. They also make it easier to manage and update large databases, as changes to a domain can be made in one place and automatically applied to all columns that use that domain.

NULL Values: In a relational database, a NULL value is a special marker used to indicate that a data value does not exist in the database. It is used to represent missing or unknown information in a record. A NULL value can be inserted into a table for a particular attribute when the information is not available or is not applicable.

For example, in a customer table, if a particular customer does not have a phone number associated with them, the phone number attribute for that customer may be given a NULL value. Similarly, if a customer has not made any purchases, the purchase history attribute may be given a NULL value.

It is important to note that NULL values are not the same as zero, blank or empty strings, or any other type of value. NULL values cannot be compared using the usual comparison operators such as =, <, or >, as their value is unknown. To check for NULL values in a table, the IS NULL or IS NOT NULL operator is used.

The use of NULL values in a database can be a powerful tool for representing missing or unknown data, but it can also add complexity to queries and require careful handling in application code.

Primary Key: In a Relational Database Management System (RDBMS), a Primary Key is a column or set of columns that uniquely identifies each record or row in a table. It is a special type of constraint that ensures the uniqueness of each row in the table and helps to enforce data integrity.

The primary key can be a single column or a combination of columns, but it must satisfy the following conditions:

  1. It must contain unique values for each row in the table.
  2. It must not contain null values.
  3. It should be stable, i.e., it should not change frequently.

Commonly, the primary key is created using an auto-incrementing column or a unique identifier such as a Social Security Number or an email address.

Primary keys are essential in relational database design as they help to establish relationships between tables and ensure data consistency. Other tables can use the primary key of a table as a foreign key to link records between tables.

Foreign Key: In a Relational Database Management System (RDBMS), a Foreign Key is a column or set of columns in one table that refers to the Primary Key of another table. It is a way of establishing a relationship between two tables in a database.

A foreign key is used to maintain data consistency between related tables by ensuring that data entered into the referencing table must match data in the referenced table. This is achieved through a constraint that enforces referential integrity between the tables.

The foreign key constraint requires that:

  1. The values in the referencing column or columns of one table must match the values in the Primary Key column or columns of the referenced table, or be NULL.
  2. The referenced Primary Key column or columns must be unique, i.e., no two rows in the referenced table can have the same Primary Key value.

Foreign keys are essential in database design, as they help to establish relationships between tables and ensure data consistency. They enable database designers to create complex, normalized databases that can handle large amounts of data efficiently. When used correctly, foreign keys help prevent data inconsistencies, duplication, and other data quality issues.

  1. Index: An index is a data structure that is used to improve the performance of database queries. It is created on one or more columns of a table and provides a faster way to retrieve data from the table.
  2. Query: A query is a request for data from a database. It is used to retrieve, filter, and sort data from one or more tables in a database.
  3. Transaction: A transaction is a sequence of database operations that are performed as a single unit of work. Transactions are used to ensure data consistency and to prevent data corruption.
  4. ACID: ACID is an acronym for Atomicity, Consistency, Isolation, and Durability. It is a set of properties that guarantee that database transactions are processed reliably.
  5. Normalization: Normalization is the process of organizing data in a database in a way that reduces redundancy and ensures data integrity. It is achieved by dividing larger tables into smaller, more specific tables and defining relationships between them.

These terminologies are fundamental to understanding how an RDBMS works and are essential for designing, implementing, and maintaining a relational database system.

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