What is SQL Used For? Key Applications and Benefits Explainedd

Ever wondered, "What is SQL used for?" You’re in the right place. SQL, or Structured Query Language, is a standardized programming language widely adopted for managing and manipulating data in relational database management systems (RDBMS).

From analyzing data to running a cloud database or handling stored procedures, SQL is a critical tool in your developer toolkit. Let’s break down why it’s such a key part of modern development workflows.

What is SQL? A quick overview

SQL is a standardized programming language built for interacting with relational databases — systems that store data in highly organized tables. Think of these tables as structured grids where information is kept tidy and accessible. Structured query language allows you to retrieve and manipulate data, and run database queries efficiently.

First introduced by IBM in the 1970s, SQL quickly became a global standard, earning recognition from the American National Standards Institute (ANSI) and the International Organization for Standardization (ISO). Its longevity speaks to its reliability and adaptability. SQL operates as the bridge between users and RDBMS like:

• Microsoft SQL Server
• PostgreSQL
• MySQL

A relational database management system is designed to manage data stored in a relational format for easy access and data manipulation.

How SQL works: the basics of database interaction

When you execute an SQL query, it is processed by the database’s query processor, and then takes your command, interprets it, and translates it into actions the database can perform. This interaction typically involves a server machine, which hosts the database and handles requests from users or applications.

1. Parser: The query is first analyzed for syntax and semantics. The parser checks if the SQL statement follows the correct rules and identifies the structure of the request.
2. Optimizer: The optimizer evaluates different ways to execute the query and chooses the most efficient plan. For example, it might decide to use an index to speed up data retrieval instead of scanning the entire table.
3. Execution engine: Finally, the execution engine carries out the optimized plan by interacting with the database storage, retrieving or modifying data as needed.

Imagine you want a list of customers from a specific city. Your query goes through the query processor, which analyzes what you’ve requested and figures out the most efficient way to retrieve the data. Once it gathers the relevant information from the database tables, the server sends the results back in a structured format.

Relational databases store data in rows and columns. Each table represents an entity – like customers, orders, or products. These tables connect through keys, creating relationships that make querying and organizing data simple.

Core capabilities of SQL

SQL’s capabilities can be grouped into four main categories, collectively referred to as SQL's sublanguages. In addition, SQL also supports query optimization.

1. Retrieving data

Data Query Language (DQL) is the foundation of SQL’s utility, allowing you to extract data stored in relational databases. At its core is the SELECT command, which retrieves data from database tables based on your criteria.

SELECT name, email FROM customers WHERE country = 'USA';

DQL's ability to filter, aggregate, and organize data makes it essential for building reports and generating actionable insights.

2. Modifying database objects

Data Definition Language (DDL) focuses on defining and modifying the structure of database objects, such as tables, indexes, and views. With commands like CREATE, ALTER, and DROP, DDL allows you to set up and customize relational databases to meet the specific needs of your application or business.

CREATE TABLE orders (
  order_id INT PRIMARY KEY,
  order_date DATE,
  total_amount DECIMAL(10, 2)
);

DDL doesn’t interact with the data itself but lays the foundation for how it’s stored, accessed, and structured. From creating the database structure and tables to adjusting column formats, DDL is what makes your database flexible and scalable.

3. Manipulating data

Data Manipulation Language (DML) allows you to directly interact with the data within your database. With commands like INSERT, UPDATE, and DELETE, DML enables you to add new records, modify existing ones, or remove outdated information.

INSERT INTO orders (order_id, order_date, total_amount)

DML ensures your database remains accurate and up-to-date, handling tasks like updating inventory levels, processing transactions, or maintaining user profiles. It plays a key role in day-to-day data management and supports dynamic applications where information changes frequently.

4. Controlling access

Data Control Language (DCL) focuses on managing security and permissions within SQL databases. Commands like GRANT and REVOKE help administrators enforce security policies and control access to sensitive data.

GRANT SELECT ON customers TO user_readonly;

This functionality is crucial for database administrators to maintain data privacy and ensure compliance with security standards.

5. Optimizing database performance

Efficient query execution is critical to keeping your SQL database responsive and reliable. Query optimization minimizes resource usage, reduces execution time, and ensures your database performs well even under heavy workloads.

To achieve this, focus on writing efficient SQL queries by reducing unnecessary complexity, analyzing execution plans to identify bottlenecks, and using indexes strategically to speed up data retrieval. Some best practices include:

• Creating indexes on frequently queried columns, especially those used in JOIN, WHERE, or ORDER BY clauses. Avoiding over-indexing, as it can slow down write operations.
• Reviewing the query execution plan to identify inefficiencies like full table scans or redundant operations. Adjusting queries or indexes based on these insights.
• Only retrieving the data you need. Instead of using SELECT *, specify columns explicitly to reduce data transfer and improve query speed.
• Breaking large tables into smaller, more manageable partitions based on criteria like date ranges or regions. This limits the data the query engine scans.

The six most useful SQL commands

When working with an SQL database, mastering a handful of essential SQL statements can take you a long way. The following SQL commands let you write SQL queries to retrieve records, update values, or combine information from multiple tables.

1. SELECT: Retrieving data

The SELECT statement is the most commonly used SQL command. It allows you to specify which columns of data you want to retrieve from a database table. You can narrow down your search using the WHERE clause to filter rows based on specific conditions.

SELECT first_name, last_name
FROM employees
WHERE department = 'Sales';

2. INSERT: Adding new data

The INSERT statement adds new rows of data to a SQL table. You specify the table name, the columns to populate, and the corresponding data values.

INSERT INTO customers (customer_id, name, email)
VALUES (101, 'John Doe', 'john.doe@example.com');

In the above example, INSERT INTO specifies the table (customers) to which data is added, and VALUES provides the data for each column in the specified order.

3. UPDATE: Modifying existing records

The UPDATE statement changes existing data in a database table. It uses the SET clause to define new values and the WHERE clause to target specific rows.

UPDATE customers
SET email = 'jane.doe@example.com'
WHERE customer_id = 101;

Here, UPDATE modifies the customer's table, SET specifies the new value for the email column, and WHERE ensures that only the record with customer_id 101 is updated.

4. DELETE: Delete data

The DELETE statement removes rows from a database table. Use the WHERE clause carefully to specify which rows should be deleted. Without it, all rows in the table will be removed.

DELETE FROM customers
WHERE customer_id = 101;

5. JOIN: Combining data from multiple tables

SQL allows you to combine data from multiple database tables using a JOIN. This is essential in relational databases, where data is spread across related tables.

SELECT orders.order_id, customers.name
FROM orders
JOIN customers ON orders.customer_id = customers.customer_id;

In this case, JOIN connects the orders and customers tables, while the ON clause specifies the relationship between the two tables.

6. CREATE: Define objects in the database

The CREATE statement is the foundation for building an SQL database. It allows you to create database objects, such as tables, indexes, or entire databases.

For example, to create a table for customer data:

CREATE TABLE customers (
    customer_id INT PRIMARY KEY,
    name VARCHAR(100) NOT NULL,
    email VARCHAR(255) UNIQUE NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

More SQL commands to know

If you want to familiarize yourself with some additional SQL commands that will provide a deeper level of control, here's a quick list:

• ALTER: Modifies the structure of an existing table, such as adding or deleting columns.
• DROP: Permanently deletes a table, database, or another database object.
• TRUNCATE: Removes all rows from a table but keeps the structure intact.
• GRANT: Assigns specific permissions to users on objects in the database.
• REVOKE: Removes permissions from a user on objects in the database.
• CREATE VIEW: Creates a reusable virtual table based on a query.
• INDEX: Adds an index to a table column to improve query performance.
• DISTINCT: Ensures that a SELECT query returns unique values only.
• HAVING: Filters aggregated results after a GROUP BY operation.
• UNION: Combines the result sets of multiple SELECT queries.
• EXISTS: Tests for the existence of rows meeting specific criteria.
• CASE: Introduces conditional logic into queries.
• SAVEPOINT: Creates a rollback point within a transaction.
• ROLLBACK: Reverses changes made during a transaction.
• COMMIT: Finalizes and saves changes made during a transaction.

Applications of SQL across industries

SQL’s versatility makes it indispensable across numerous industries, serving as the backbone for managing and manipulating data. From enabling advanced analytics to supporting critical software infrastructure, structured query language is at the core of modern data systems.

Let’s explore its most impactful applications:

Data science and analytics

Data professionals rely on SQL to extract, clean, and prepare data for advanced analysis. SQL’s data query language capabilities make it great for tasks like customer segmentation, financial forecasting, and exploratory data analysis in industries ranging from retail to healthcare.

For example, a marketing team uses SQL to analyze customer purchase trends by querying database tables to determine the top-performing products and forecast future demand. By manipulating data through DML commands, they prepare datasets for visualization tools like Tableau or modeling in Python and R.

Software development

For developers, SQL is the connection between the user interface and the data driving it. Alongside database engineers, developers use SQL to design efficient schemas, manage relationships, and maintain application performance.

Just consider how SQL powers an ecommerce platform. It manages user authentication by securely storing and validating customer credentials during login. It drives product browsing, allowing users to search and filter items by category, price, or popularity. When it comes to order processing, SQL offers consistency by handling transactions like updating inventory levels and recording payment details while maintaining data integrity.

Developers often integrate SQL with Python or JavaScript frameworks to build modern, data-driven features.

Database administration

DBAs are responsible for designing and maintaining database structures, such as creating tables, indexes, and relationships to store data effectively. They also configure and enforce access controls using DCL commands.

Another critical role is optimizing query performance. DBAs use tools like query processors and execution plans to identify bottlenecks, add indexes, and refine SQL statements for faster, more efficient data retrieval. Beyond day-to-day management, they also handle backups, recovery plans, and system updates.

Business intelligence and reporting

In business intelligence (BI), SQL is key for generating reports and dashboards that support decision-making. BI tools like Power BI and Looker rely on SQL systems to connect to relational software and fetch the data needed for analysis.

A sales team might use SQL to generate monthly performance reports by querying sales data across multiple cloud databases. The result is a real-time dashboard showing revenue, conversions, and customer retention rates.

Why you should learn SQL

Think about how often you hear the phrase "data-driven." Data is the lifeblood of modern businesses, and SQL is the standard language that keeps it flowing. Behind every dashboard, report, and application making sense of that data, there’s SQL. It's truly a must-have skill for developers and data professionals.

Versatility across platforms

SQL works across almost every major database platform out there — MS SQL Server, MS Access MySQL, PostgreSQL — you name it. This consistency lets you work with different systems without needing to learn a new language every time. If you learn SQL, you open up a whole world of possibilities.

However, what sets SQL apart is how easily it connects with the tools and languages you’re already using. Need to build a dashboard? Pair SQL with Power BI or Tableau to transform raw data into something clients can actually use. Prepping data for a Python script? SQL can pull exactly what you need.

Even in app development, SQL works seamlessly with programming languages like Java or C#, powering things like real-time user data and backend analytics.

Career growth

SQL skills are highly in demand across roles like database engineers, data analysts, and software developers. Proficiency in SQL enhances job prospects and boosts earning potential, as businesses prioritize efficient data processing tasks and query optimization.

The demand for SQL knowledge translates directly into competitive salaries. For instance, data analysts with SQL skills earn an average of $74,377 per year, while SQL developers have an average salary of $91,927 per year.

Adaptability beyond relational databases

SQL has evolved far beyond its original use in relational database management systems. Today, it’s adapted for non-relational databases, hybrid systems, and even cloud-native platforms like AWS and Azure, where it powers scalable, distributed data operations.

For example, AWS Redshift and Google BigQuery use SQL-like syntax to query massive datasets in cloud environments. SQL’s flexibility also allows it to work alongside modern NoSQL databases like MongoDB or Cassandra, bridging the gap between structured and unstructured data.

How the Text Platform supports SQL users

If SQL is the backbone of your solutions, the Text Platform has your back. It’s built to help developers seamlessly connect their relational databases to powerful, real-world applications. The Text Platform offers:

• APIs and SDKs: With APIs for chat messaging, reporting, and configuration, you can connect your SQL databases to your apps without the usual headaches.
• Innovation-ready features: Want to go beyond basic database functionality? Text Platform’s APIs let you tackle advanced text operations and build apps that leverage real-time data.
• A built-in audience: Publish your SQL-powered apps on the Text Marketplace, tap into an established customer base, and earn passive income.

Start building smarter, faster, and with more impact — sign up for Text Platform today.