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What is SQL (Structured Query Language)? – A Complete Guide

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SQL, known as the Structured Query Language, is a programming language that is often used to communicate with databases. It helps to maintain and manipulate information stored in relational databases. As such, SQL is an invaluable set of tools for anyone who works with data as it allows him or her to perform various operations like inserting, updating, deleting and retrieving information.

This blog will discuss what SQL is, its history, why it is necessary and the various parts that make up a SQL system. We will also learn details about the workings of SQL, the command set available to SQL users, SQL injection, SQL servers and applications of SQL.

What is SQL?

Structured Query Language (SQL) is a programming language designed specifically for managing and manipulating relational databases. Using a series of commands this allows users to interact with the data stored in these databases. These commands perform several functions including querying data from tables, inserting new records into existing tables, updating pre-existing records in such tables or even deleting them completely. From basic data retrieval tasks to complex analysis processes within many industries, effective database management cannot be achieved without using SQL.

SQL operates based on a simple yet powerful syntax, making it accessible to both beginners and experienced programmers. For instance, ‘SELECT * FROM Employees’ would retrieve all records from a table named “Employees”. This simplicity has made sure that there has been good uptake and usage of SQL over time.

Although closely associated with relational databases, the principles behind SQL can be applied across various types of modern application databases as well. Over the years, several features were added that supported complex queries, making it versatile for use in more than just one kind of environment. Whether you are managing small datasets or working with large-scale enterprise systems, SQL provides the tools needed to efficiently interact with your data.

History of SQL

It was first developed by Donald D. Chamberlin and Raymond F. Boyce at IBM during the 1970s and was originally named SEQUEL (Structured English Query Language) for managing and manipulating data in early relational database systems by IBM. However, because of trademark issues, it was later renamed to SQL.

Over time, SQL quickly became popular as it evolved into a standard language for relational databases. In 1986, the American National Standards Institute adopted it as a standard for Database management systems. Since then, different versions of the SQL language have been added to meet new demands, resulting from increased use of data.

Why is SQL important?

SQL is critical for efficient handling and retrieval of information from a relational database system. It provides several advantages:

Data Management: Storing, retrieving or updating records could be done in parallel, saving on transaction time such that more transactions can be processed per unit of time.
Standardisation: As the standard language for relational databases, SQL provides consistency across different database systems.
Data Analysis: It is used in complex queries which help in data analysis and reporting, making it an essential component of business intelligence.
Scalability: SQL can be employed over both big and small datasets, thus suitable for a wide range of uses from small businesses to large enterprises.
Interoperability: The versatility of SQL derived from the capability to interact with different programming languages and tools.

What are the components of a SQL system?

An SQL system is composed of several fundamental components that work together to perform database operations. Understanding these components is crucial for effectively writing and executing SQL queries. In this section, we will delve into the five key components of a SQL system:

Keywords
Clauses
Expressions
Predicates
Queries

Each of these components plays a specific role in how SQL interacts with databases. Let’s explore these components in detail.

1. Keywords

SQL language has special meanings for reserved words called keywords which are used in SQL commands as basic units that act on data in databases. These keywords are predefined and cannot be assigned to any other function such as naming database objects like tables, columns or indexes. Having an understanding of keywords is important when writing correct SQL statements for accessing a database.

Role and Use of Keywords

Keywords specify what actions will be performed by SQL commands. For instance, ‘SELECT’ is used to retrieve data from a database while ‘INSERT’ adds new records into tables. Each keyword performs a specific task and they are often combined to form whole SQL statements like ‘SELECT * FROM Employees’.

Common SQL Keywords

Here’s a table of some commonly used SQL keywords and their functions:

Keyword	Function
SELECT	Retrieves data from one or more tables
INSERT	Adds new records to a table
UPDATE	Modifies existing records in a table
DELETE	Removes records from a table
FROM	Specifies the table(s) to retrieve data from
WHERE	Filters records based on a condition
JOIN	Combines records from multiple tables

Example of SQL Keyword Use

Here’s an example of how keywords are used in a SQL query:

SELECT name, age FROM Employees WHERE age > 30;

In this query, SELECT, FROM, and WHERE are all keywords. This query retrieves the “name” and “age” of employees who are older than 30 years.

2. Clauses

Clauses refer to individual components of a SQL statement that determine under what conditions the manipulation operation within the SQL should take place. They define how data should be retrieved, added, updated or deleted in a structured way by facilitating users to control their queries appropriately. Each clause plays its own role and several clauses can be united in complex ways to come up with intricate SQL sentences.

Role and Use of Clauses

These help refine what action is being asked for by the keywords. An example is ‘WHERE’ which allows you to filter records based on certain defined criteria or ‘ORDER BY’ sorts results into specified orders accordingly. Think of them as modifiers that fine-tune the basic query language instructions, hence allowing more control over manipulated information/data. Without clauses, SQL commands would lack specificity, making them less useful for practical applications.

Common SQL Clauses

Below is a table of commonly used SQL clauses and their functions:

Clause	Function
WHERE	Filters records based on a specified condition
ORDER BY	Sorts the result set in ascending or descending order
GROUP BY	Groups records that have the same values in specified columns
HAVING	Filters groups based on a condition
LIMIT	Restricts the number of records returned by a query

Example of SQL Clause Use

Here’s an example of a SQL query using clauses:

SELECT name, salary FROM Employees WHERE salary > 50000 ORDER BY salary DESC;

In this query, WHERE and ORDER BY are clauses. The WHERE clause filters employees with a salary greater than 50,000, and the ORDER BY clause sorts the results in descending order based on salary.

3. Expressions

Expressions in SQL are combinations of symbols, operators, and values that evaluate to a single value. They are used to perform calculations, comparisons, and other operations within SQL statements. Expressions can contain constants, column names, functions and operators. Understanding expressions is important because they enable you to change data dynamically and derive new information from the stored data.

Role and Use of Expressions

Expressions are commonly used in SQL to compute values and make decisions based on those values. These may involve calculating the total price of items in an order by multiplying a quantity by price or checking if a particular record meets certain conditions. Expressions can be as simple as basic arithmetic operations or very complex, involving many operators and functions.

Types of SQL Expressions

Here’s a table of common types of SQL expressions and their uses:

Expression Type	Function
Arithmetic	Performs mathematical calculations (e.g., +, -, *, /)
String	Manipulates string data (e.g., concatenation using `
Boolean	Evaluates to TRUE, FALSE, or NULL
Date	Performs operations on date values (e.g., adding days)
Comparison	Compares two values (e.g., =, <, >)

Example of SQL Expression Use

Here’s an example of how an expression is used in a SQL query:

SELECT name, salary * 12 AS annual_salary FROM Employees;

In this query, salary * 12 is an arithmetic expression that calculates the annual salary by multiplying the monthly salary by 12.

4. Predicates

Predicates consider whether a condition holds true, false or unknown (null). They specify what type of conditions should be met for specific operations such as filtering data with where clauses, or deciding upon which records will be used in join operation. Predicates are key components of SQL since they enable users to deal with some part of the data required under definite conditions.

Role and Use of Predicates

A predicate is often used to restrict the data selection in a clause. For instance, a predicate may indicate that only records with a salary higher than fifty thousand should be included in the result set. Through predicates, more precise queries can be formulated that return only the required data, thereby, making database operations more efficient and focused.

Common SQL Predicates

Here’s a table of common SQL predicates and their purposes:

Predicate	Function
=	Checks if two values are equal
<> or !=	Checks if two values are not equal
>	Checks if the left value is greater than the right value
<	Checks if the left value is less than the right value
BETWEEN	Checks if a value is within a specified range
IN	Checks if a value matches any value in a list
LIKE	Checks if a value matches a pattern
IS NULL	Checks if a value is NULL

Example of SQL Predicate Use

Here’s an example of an SQL query using a predicate:

SELECT name, department FROM Employees WHERE salary > 50000 AND department = 'Sales';

In this query, salary > 50000 and department = ‘Sales’ are predicates used to filter employees who have a salary greater than 50,000 and work in the Sales department.

5. Queries

A query in SQL is a means by which one can request information or data from the database where it resides. Users interact with a database mostly through queries where they are able to retrieve, modify, insert or delete data from it. At times these may be relatively straightforward like pulling all records from a table, while other times may involve combining different sets of data and filtering them based on varied criteria. After that, some calculations are performed on the resultant outcomes obtained from such cases. Knowing how to create effective queries will be very useful when working with databases.

Role and Use of Queries

Queries are at the core of SQL functionality. They are used for specific searches, during updates of records as well as the creation of reports among other activities that require you to speak to the database to get what you need from there. SQL queries follow a structured syntax that typically includes keywords, clauses, expressions, and predicates to define the exact operation you want to perform.

Components of SQL Queries

Here’s a table summarising the key components of a SQL query:

Component	Function
SELECT	Specifies the columns to retrieve
FROM	Specifies the table(s) to retrieve data from
WHERE	Filters records based on a condition
JOIN	Combines rows from two or more tables
ORDER BY	Sorts the result set in ascending or descending order
GROUP BY	Groups records that have the same values in specified columns
HAVING	Filters groups based on a condition

Example of SQL Query

Here’s an example of a complete SQL query:

SELECT department, COUNT(*) AS employee_count

FROM Employees

WHERE salary > 50000

GROUP BY department

HAVING COUNT(*) > 5

ORDER BY employee_count DESC;

In this query, we are retrieving the count of employees in each department where the salary is greater than 50,000, and only including departments with more than five employees. The results are then sorted in descending order by employee count.

How does SQL work?

Below are the steps involved in executing an SQL Query step by step.

Step 1: Establishing a connection

SQL starts by creating a connection with a database. This is done through Database Management System (DBMS) such as MYSQL, PostgreSQL, etc.
Credentials like username, password and database name will be required for connecting.

Step 2: Write an SQL Query

A particular purpose makes one write an SQL query which could either be extracting information from the dataset, updating existing data, adding new ones, or deleting some.
The composition of this input includes keywords, clauses, expressions, predicates, etc.

Step 3: Submit the Query

Once the query is written, it is submitted to the database through the DBMS. Then, DBMS processes the query.

Step 4: Query Parsing

The DBMS parses the SQL query to ensure it is syntactically correct.
During parsing, the query is checked for errors, such as incorrect keywords or missing clauses.

Step 5: Query Optimization

Once parsing is completed, the DBMS optimises the query for efficiency.
Optimization includes the selection of appropriate paths and algorithms to access the data.

Step 6: Query Execution

The optimised query is now executed by the DBMS.
During the execution stage, the DBMS retrieves or modifies the data as stated in the query.

Step 7: Fetching the Result

When a query is performed, it returns results that are fetched from the database by DBMS.
While performing a SELECT query this may mean returning rows of data. For an INSERT, UPDATE, or DELETE query, this might involve confirming that the operation was successful.

Step 8: Return the Result to the User

The results of a query are sent back to whoever submitted it i.e. either the user or application in the form of a screen display.

Step 9: Close Connection

At last, the connection is closed after everything has been carried out on it concerning one specific operation being complete.

Examples of SQL Queries

To understand how SQL works in practice, let’s start by creating a table, inserting some records into it, and then executing various SQL queries to manipulate and retrieve data.

Creating and Populating a Table

First, we’ll create a table named Employees to store information about employees.

CREATE TABLE Employees (

employee_id INT PRIMARY KEY,

name VARCHAR(50),

department VARCHAR(50),

salary INT,

hire_date DATE

);

Next, we insert some records into the Employees table:

INSERT INTO Employees (employee_id, name, department, salary, hire_date) VALUES

(1, 'Alice', 'HR', 60000, '2020-05-15'),

(2, 'Bob', 'Finance', 75000, '2019-03-10'),

(3, 'Charlie', 'IT', 80000, '2021-08-22'),

(4, 'Diana', 'Marketing', 65000, '2020-11-01'),

(5, 'Evan', 'Finance', 72000, '2018-07-14');

Now, the Employees table looks like this:

employee_id	name	department	salary	hire_date
1	Alice	HR	60000	2020-05-15
2	Bob	Finance	75000	2019-03-10
3	Charlie	IT	80000	2021-08-22
4	Diana	Marketing	65000	2020-11-01
5	Evan	Finance	72000	2018-07-14

Query 1: Retrieve All Records

To retrieve all records from the Employees table, we use the SELECT statement:

SELECT * FROM Employees;

Result:

employee_id	name	department	salary	hire_date
1	Alice	HR	60000	2020-05-15
2	Bob	Finance	75000	2019-03-10
3	Charlie	IT	80000	2021-08-22
4	Diana	Marketing	65000	2020-11-01
5	Evan	Finance	72000	2018-07-14

This query returns all columns and rows from the Employees table.

Query 2: Filter Records with a WHERE Clause

To filter employees with a salary greater than 70,000, we use the WHERE clause:

SELECT name, department, salary FROM Employees WHERE salary > 70000;

Result:

name	department	salary
Bob	Finance	75000
Charlie	IT	80000
Evan	Finance	72000

This query retrieves the names, departments, and salaries of employees earning more than 70,000.

Query 3: Sorting Records with ORDER BY

To sort the employees by salary in descending order, we use the ORDER BY clause:

SELECT name, department, salary FROM Employees ORDER BY salary DESC;

Result:

name	department	salary
Charlie	IT	80000
Bob	Finance	75000
Evan	Finance	72000
Diana	Marketing	65000
Alice	HR	60000

This query sorts the records based on the salary column in descending order.

Query 4: Grouping Records with GROUP BY

To find the average salary by department, we use the GROUP BY clause:

SELECT department, AVG(salary) AS average_salary FROM Employees GROUP BY department;

Result:

department	average_salary
Finance	73500
HR	60000
IT	80000
Marketing	65000

This query groups employees by department and calculates the average salary for each department.

Query 5: Filtering Groups with HAVING

To filter out departments with an average salary below 70,000, we use the HAVING clause:

SELECT department, AVG(salary) AS average_salary FROM Employees GROUP BY department HAVING AVG(salary) >= 70000;

Result:

department	average_salary
Finance	73500
IT	80000

This query filters the groups to include only those departments where the average salary is 70,000 or higher.

Query 6: Using JOIN to Combine Data from Multiple Tables

Let’s assume we have another table called Departments that includes the department head names:

CREATE TABLE Departments (

department VARCHAR(50),

head VARCHAR(50)

);

INSERT INTO Departments (department, head) VALUES

('HR', 'Megan'),

('Finance', 'John'),

('IT', 'Lisa'),

('Marketing', 'Tom');

To retrieve employee names along with their department heads, we use the JOIN clause: 

SELECT Employees.name, Employees.department, Departments.head 

FROM Employees 

JOIN Departments ON Employees.department = Departments.department;

 

<strong>Result:</strong>

name	department	head
Alice	HR	Megan
Bob	Finance	John
Charlie	IT	Lisa
Diana	Marketing	Tom
Evan	Finance	John

This query combines data from the Employees and Departments tables based on the department column.

Query 7: Updating Records

To give a 10% salary raise to all employees in the IT department, we use the UPDATE statement:

UPDATE Employees SET salary = salary * 1.10 WHERE department = 'IT';

Result:

After executing this query, the salary for Charlie, who is in the IT department, will be updated to 88,000.

Updated Employees Table:

employee_id	name	department	salary	hire_date
1	Alice	HR	60000	2020-05-15
2	Bob	Finance	75000	2019-03-10
3	Charlie	IT	88000	2021-08-22
4	Diana	Marketing	65000	2020-11-01
5	Evan	Finance	72000	2018-07-14

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What is SQL injection?

SQL injection is a security vulnerability where an attacker inserts malicious SQL code into a query. This happens when user inputs are not properly sanitised, allowing attackers to manipulate the database. For example, entering ‘ OR ‘1’=’1 in a login field could allow unauthorised access.

Consequences:

Data Breach: Attackers can steal sensitive information.
Data Manipulation: Attackers can alter or delete data.
System Compromise: The entire database and server could be at risk.

Prevention:

Use Prepared Statements: These prevent SQL code injection.
Validate Input: Ensure user inputs are safe.
Limit Permissions: Reduce the impact of potential attacks.

What is an SQL server?

SQL Server is a relational database management system (RDBMS) by Microsoft. It stores, manages, and retrieves data for applications, supporting everything from small programs to large enterprises.

Key Features:

Relational Database Management: Structured data storage and retrieval.
T-SQL: Enhanced SQL language used by SQL Server.
Scalability: Suitable for small to large systems.
Security: Strong data protection features.

Components:

Database Engine: Core service for data processing.
SQL Server Agent: Automates administrative tasks.
SSRS: Reporting tool.
SSIS: Platform for data integration.

Applications of SQL

Due to its flexibility and effectiveness in managing relational databases, SQL has been widely applied across numerous industries. Below are some major uses:

Data Management: In dealing with large amounts of structured data, SQL plays an important role. It helps users insert, update, delete, and retrieve specific information that will later form part of their relational DBs.
Data Analysis and Reporting: SQL is used to generate reports and perform data analysis. Businesses use SQL to query databases and extract meaningful insights from data, which helps in decision-making processes.
Web Development: The web applications that are based on SQL can be used to create dynamic content by working with databases. For instance, in social media sites and e-commerce platforms, SQL queries are responsible for fetching user data.
Database Administration: As one of the DBA’s most important tools, SQL allows for backup, recovery and managing security issues. They support database integrity, maintenance, and performance optimization activities using it.
Business Intelligence: SQL is used for developing business intelligence tools that collect and analyse information from various sources. This includes generating dashboards that track key performance indicators (KPIs).
Financial Systems: In financial institutions, SQL is extensively applied to manage transactions, and customer details as well as prepare financial reports, among others. It ensures there is data accuracy and consistency within a financial database.

Pros and Cons of SQL

Pros:

Standardised Language: SQL is widely accepted, making it easier to use across different platforms.
Data Integrity: Ensures accuracy and consistency of data with constraints and relationships.
Ease of Use: Simple syntax resembling English makes it beginner-friendly.
Versatile: Capable of handling various tasks, from basic queries to complex transactions.
Security Features: Offers robust security measures, including user access control and data encryption.

Cons:

Complex for Large Databases: Handling large datasets requires careful optimization, which can become challenging.
Limited Scalability: Struggles with horizontal scaling, especially with distributed databases.
Fixed Schema: Requires a predefined structure, which is less flexible for dynamic or unstructured data.
Performance Issues with Complex Queries: Queries with multiple joins can slow down database performance.
Vendor Lock-In: Some SQL systems are vendor-specific, which may limit portability between platforms.

SQL vs. MySQL – Explaining Differences

Feature	SQL	MySQL
Definition	SQL is a standard language for querying and managing relational databases.	MySQL is an open-source RDBMS that uses SQL as its primary query language.
Usage	SQL is used in various RDBMSs like SQL Server, Oracle, PostgreSQL, and MySQL.	MySQL is specifically a database management system, not just a language.
Licensing	SQL itself does not have licensing; it’s a standard.	MySQL offers both open-source and commercial licences.
Performance	Performance depends on the specific SQL implementation (e.g., SQL Server, Oracle).	MySQL is known for its speed, especially in read-heavy operations.
Flexibility	SQL standards are rigid; each RDBMS may add proprietary extensions.	MySQL offers various storage engines and is highly configurable.
Support for Transactions	Depends on the RDBMS (e.g., SQL Server supports transactions fully).	MySQL supports transactions but with specific storage engines like InnoDB.
Scalability	Generally good but can vary depending on the SQL implementation and architecture.	MySQL is scalable but may require additional tools for complex scaling needs.

SQL vs. NoSQL – Explaining Differences

Feature	SQL	NoSQL
Data Model	Relational, table-based with a fixed schema.	Non-relational, can be document-based, key-value, wide-column, or graph.
Schema	Fixed schema; structure must be defined before data entry.	Dynamic schema; flexible, can accommodate unstructured data.
Scalability	Vertical scalability; scaling usually involves upgrading hardware.	Horizontal scalability; can easily scale across multiple servers.
Query Language	Uses SQL as the standard query language.	No standardised query language; varies by database (e.g., MongoDB uses BSON, Cassandra uses CQL).
Transactions	Strong support for ACID transactions (Atomicity, Consistency, Isolation, Durability).	Varies by database; some NoSQL databases offer limited or eventual consistency, prioritising availability and partition tolerance.
Use Cases	Ideal for structured data, complex queries, and multi-row transactions.	Ideal for handling large volumes of unstructured or semi-structured data, and for applications requiring high scalability and performance.
Examples	SQL Server, MySQL, PostgreSQL, Oracle.	MongoDB, Cassandra, Couchbase, DynamoDB.
Performance	Performance can be limited by the complexity of queries and joins.	Optimised for performance in large, distributed systems, often sacrificing some consistency for speed.
Flexibility	Less flexible due to strict schema requirements.	Highly flexible, allowing for rapid development and iteration.

Conclusion

SQL continues to be an important tool in the management of relational databases. Its standardised syntax makes it easy to use, while also providing functionalities that make it suitable for all industries. Whether the task at hand involves simple retrieval or complex transaction processing, SQL has what it takes to deal with data efficiently but safely.

As databases keep evolving so does SQL, adapting itself to new challenges while still adhering to its fundamental principles is important. Thus, having a grasp of its components, applications, and distinctions from other technologies becomes important to stay ahead in the industry.

FAQs

What is SQL?

SQL is a language used to manage and manipulate relational databases.

How does SQL differ from MySQL?

SQL is a language, while MySQL is a database management system that uses SQL.

What are the main components of SQL?

Keywords, clauses, expressions, predicates, and queries.

Is SQL still relevant today?

Yes, SQL is widely used in various industries for data management.

What is SQL injection?

A security vulnerability where attackers insert malicious SQL code into queries.

Can SQL handle large datasets?

Yes, but managing very large datasets can require careful optimization.

What is an SQL server?

An SQL Server is a relational database management system developed by Microsoft.

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