When you buy through affiliate links in our content, we may earn a commission at no extra cost to you. Learn 
What is Structured Query Language (SQL)?
SQL is a standardized programming language that is used to manage, manipulate, and query data in relational database management systems (RDBMS). Its declarative syntax is designed to be human-readable, which makes it relatively easy to learn and use.
Key Takeaways
- SQL is a programming language that allows users to interact with a relational database.
- Its declarative syntax allows users to specify what data they need without having to define the procedural steps to retrieve it.
- Most business and web applications rely on SQL-compatible databases.
- SQL is designed to work with structured data that can be organized with rows and columns within a table.
- SQL’s standardized format allows it to be used for basic operations in both proprietary and open-source database management systems with minimal changes.
SQL History
SQL was developed in the early 1970s at IBM by Donald D. Chamberlin and Raymond F. Boyce. It was originally called SEQUEL (Structured English Query Language) and was designed to manipulate and retrieve data stored in IBM’s relational database system, System R.
In the late 1970s, Oracle (then called Relational Software Inc.) released the first commercially available implementation of SQL, and by the mid-1980s, SQL had become the standard query language for all relational database systems.
By the end of the 1980s, The American National Standards Institute (ANSI) and the International Organization for Standardization (ISO) standardized SQL’s syntax to ensure greater consistency and portability across different relational database (RDB) systems.
SQL Importance
SQL’s standardization, combined with its vendor support and ease of use, has solidified its role as the customary query language for relational database management systems.
Updates that have been made to the standard since 1986 help ensure that SQL will be able to handle increasing data loads and new requirements for data management without compromising performance.
SQL Standards
The first SQL standard, ANSI SQL-86, defined the basic rules for interacting with a relational database. Since then, the standard has been revised to accommodate evolving database technologies, increasingly complex data management requirements, and the need to support more data-intensive applications – including those that support machine learning (ML) workflows.
How SQL Works
SQL has a declarative syntax that allows the user to state what operation they want to perform. The database management system (DBMS) takes the statement, analyzes it, and executes the necessary operations in the background.
Artificial intelligence (AI) tools can translate natural language into SQL queries without requiring the user to be familiar with SQL syntax. In the future, AI tools are expected to generate SQL statements for more complex database operations.
SQL Extensions
Basic SQL statements can be used to create, read, update, and delete data (CRUD). SQL extensions are additional features or commands that can enhance the functionality of a specific SQL implementation.
Essentially, the SQL standard provides a baseline for relational database operations, and database vendors add extensions to differentiate their offerings, optimize performance for their systems, or address specific use cases.
5 Key Components of a SQL System
An SQL system is the complete ecosystem that allows someone to use it when working with structured data.
Arguably, the five most important components of an SQL system are:
SQL Commands With Examples
SQL commands (also called statements) are complete units of code that instruct the database management system to perform a specific action.
Basic SQL Commands
| Command | Description | Example |
|---|---|---|
| SELECT | Retrieves data from a table. | SELECT * FROM Employees; |
| WHERE | Filters results based on conditions. | SELECT * FROM Employees WHERE Age > 30; |
| ORDER BY | Sorts the result set in ascending or descending order. | SELECT * FROM Employees ORDER BY Name ASC; |
| GROUP BY | Group rows share a property to aggregate data. | SELECT Department, COUNT(*) FROM Employees GROUP BY Department; |
| HAVING | Filters grouped data after aggregation. | SELECT Department, COUNT(*) FROM Employees GROUP BY Department HAVING COUNT(*) > 10; |
| DISTINCT | Retrieves unique values from a column. | SELECT DISTINCT Department FROM Employees; |
| Command | Description | Example |
|---|---|---|
| INSERT | Adds new data into a table. | INSERT INTO Employees (Name, Age, Department) VALUES (‘John’, 28, ‘HR’); |
| UPDATE | Modifies existing data in a table. | UPDATE Employees SET Age = 29 WHERE Name = ‘John’; |
| DELETE | Removes data from a table. | DELETE FROM Employees WHERE Name = ‘John’; |
| Command | Description | Example |
|---|---|---|
| CREATE TABLE | Creates a new table in the database. | CREATE TABLE Employees (ID INT PRIMARY KEY, Name VARCHAR(100)); |
| ALTER TABLE | Modifies an existing table structure. | ALTER TABLE Employees ADD Salary DECIMAL(10, 2); |
| DROP TABLE | Deletes a table from the database. | DROP TABLE Employees; |
| TRUNCATE TABLE | Removes all rows from a table without logging individual row deletions. | TRUNCATE TABLE Employees; |
| Command | Description | Example |
|---|---|---|
| GRANT | Provides user access privileges. | GRANT SELECT ON Employees TO User1; |
| REVOKE | Removes user access privileges. | REVOKE SELECT ON Employees FROM User1; |
| Command | Description | Example |
|---|---|---|
| COMMIT | Saves all changes made during the transaction. | COMMIT; |
| ROLLBACK | Undoes changes made during the transaction. | ROLLBACK; |
| SAVEPOINT | Creates a point in a transaction to rollback to. | SAVEPOINT sp1; |
SQL vs. MySQL & NoSQL
People often mix up SQL, MySQL, and NoSQL. All three terms share the letter “SQL” and have something to do with databases, but they describe completely different concepts:
- SQL is a query language.
- MySQL is a relational database management system owned by Oracle.
- NoSQL is a family of non-relational databases.
| SQL databases | NoSQL databases | |
|---|---|---|
| Schema | Requires a predefined schema | Schema-less or flexible schema |
| Data storage | Data is stored in structured tables (rows and columns) | Data is stored as key-value pairs, documents, wide-column stores, or graphs |
| Query language | SQL | APIs or a query language specific to the database |
| Scalability | Limited horizontal scaling | Designed for horizontal scalability |
| Transaction model | ACID-compliant | Maybe BASE-compliant |
| Best use cases | Financial systems, CRM systems, e-commerce platforms | Real-time analytics, IoT, social media, big data |
SQL Security
SQL helps enforce data integrity and security through constraints, permissions, and ACID properties:
SQL Pros and Cons
SQL is a powerful tool for managing relational databases, but like any programming language, it has limitations.
- Standardized and human-readable
- Highly efficient for managing structured data
- Has a mature ecosystem with wide vendor support and abundant resources
- Enforces data integrity through constraints and ACID properties
- Standard continues to evolve with new features and capabilities
- There are AI coding chatbots that can translate natural language into complex operations
- Lacks the full programming constructs found in procedural languages
- Complex operations can result in long queries that can be difficult to troubleshoot
- SQL support varies, with proprietary RDBMSes adding unique features
- Unvalidated user input can lead to SQL injection risks
The Bottom Line
The definition of SQL as a query language for relational databases has remained unchanged, even as the SQL standard has evolved with new features. Innovations like database-as-a-service (DaaS) have made relational databases more accessible, and AI-powered chatbots continue to broaden the language’s user base.
