Understanding SQL Standards
SQL, or Structured Query Language, is a standard language for accessing and manipulating databases. However, SQL standards have evolved over time to accommodate new features and functionalities. Here, we will explore three key SQL standards that are essential for understanding modern database management.
1. SQL-86 (SQL-1)
SQL-86, also known as SQL-1, was the first official SQL standard introduced by the American National Standards Institute (ANSI) in 1986. This standard laid the foundation for SQL syntax and basic functionalities. It introduced core concepts such as:
- Data Definition Language (DDL): Commands like
CREATE
,ALTER
, andDROP
for defining database schemas. - Data Manipulation Language (DML): Commands like
SELECT
,INSERT
,UPDATE
, andDELETE
for manipulating data. - Data Control Language (DCL): Commands like
GRANT
andREVOKE
for managing user permissions.
Example:
Creating a table using SQL-86:
CREATE TABLE Employees ( EmployeeID INT, FirstName VARCHAR(50), LastName VARCHAR(50), DepartmentID INT );
2. SQL-92 (SQL-2)
SQL-92, or SQL-2, was a significant update to the SQL standard, introduced in 1992. It expanded the capabilities of SQL by introducing new features such as:
- Joins: Including
INNER JOIN
,LEFT JOIN
,RIGHT JOIN
, andFULL JOIN
for combining data from multiple tables. - Subqueries: Allowing queries within queries to perform more complex operations.
- Transactions: Introducing the
BEGIN TRANSACTION
,COMMIT
, andROLLBACK
commands for managing database transactions.
Example:
Using a subquery to find employees with the highest salary:
SELECT FirstName, LastName FROM Employees WHERE Salary = (SELECT MAX(Salary) FROM Employees);
3. SQL:2016 (SQL-16)
SQL:2016, also known as SQL-16, is the most recent major revision of the SQL standard, published in 2016. This standard introduced several advanced features, including:
- JSON Support: Allowing databases to store and query JSON data natively.
- Temporal Data: Introducing support for time-based queries and data management.
- Row Pattern Matching: Enabling complex pattern matching within rows of data.
Example:
Querying JSON data in SQL:2016:
SELECT JSON_VALUE(json_data, '$.name') AS Name FROM Customers WHERE JSON_VALUE(json_data, '$.age') > 30;
Understanding these SQL standards is crucial for anyone aiming to become an Oracle Database SQL Certified Associate. Each standard builds upon the previous one, adding new capabilities that enhance the power and flexibility of SQL.