• These two statements are different:
  

  SELECT * FROM customers;
  SELECT * FROM "Customers";

• SQL statements are terminated only by the semicolon, meaning that more complex statements can be rendered across multiple lines, like this one:
  

  SELECT name, telephone, age
  FROM customers;

  This command selects the contents of the columns name, telephone and age in the table customers.

• SQL statements can incorporate program flow controls, meaning that a statement can incorporate table and row selection -- as in the previous example -- and then operate on the data contained in those columns. For example, the following command selects the name, telephone number and birthdate for all customers whose age is over 21:
  

  SELECT name, telephone, age
  FROM customers
  WHERE age > 21;

Most SQL implementations include support for issuing statements at the command line, through a graphical user interface, by using SQL programs or through application programming interfaces to access SQL databases using other programming languages.

Commonly used SQL commands with examples

Most SQL commands are used with operators to modify or reduce the scope of data operated on by the statement. Some commonly used SQL commands, along with examples of SQL statements using those commands, follow.

SQL SELECT. The SELECT command is used to get some or all data in a table. SELECT can be used with operators to narrow down the amount of data selected:

SELECT title, author, pub_date
FROM catalog
WHERE pub_date = 2021;

This example could be used by a publisher to select the title, author and publication date columns from a table named catalog.

SQL CREATE. The CREATE command is used to create a new SQL database or SQL table. Most versions of SQL create a new database by creating a new directory, in which tables and other database objects are stored as files.

The following CREATE DATABASE statement creates a new SQL database named Human_Resources:

CREATE DATABASE Human_Resources;

The CREATE TABLE command is used create a table in SQL. The following statement creates a table named Employees that has three columns: employee_ID, last_name and first_name, with the first column storing integer (int) data and the other columns storing variable character data of type varchar and a maximum of 255 characters.

CREATE TABLE Employees (
    employee_ID int,
    last_name varchar(255),
    first_name varchar(255)
);

SQL DELETE. The DELETE command removes rows from a named table. In this example, all records of employees with the last name Smithee are deleted:
DELETE FROM Employees WHERE last_name='Smithee';
This statement returns the number of rows deleted when it finishes running.
SQL INSERT INTO. The INSERT INTO command is used to add records into a database table. The following statement adds a new record into the Employees table:
INSERT INTO Employees (
    last_name,
    first_name
)
VALUES (
    'Alan',
    'Smithee'
);
SQL UPDATE. The UPDATE command is used to make changes to rows or records in a specific table. For example, the following statement updates all records that include a last_name value of Smithee by changing the name to Smith:
UPDATE Employees
SET last_name = 'Smith',
WHERE last_name = 'Smithee';
SQL statements can use loops, variables and other components of a programming language to update records based on different criteria.
SQL-on-Hadoop tools
SQL-on-Hadoop query engines are a newer offshoot of SQL that enable organizations with big data architectures built around Hadoop data stores to use SQL as a querying language and enable database professionals to use a familiar query language instead of having to use more complex and less familiar languages -- in particular, the MapReduce programming environment for developing batch processing applications.
More than a dozen SQL-on-Hadoop tools are available from Hadoop distribution providers and other vendors; many of them are open source software or commercial versions. In addition, the Apache Spark processing engine, which is often used in conjunction with Hadoop, includes a Spark SQL module that similarly supports SQL-based programming.
Not all SQL-on-Hadoop tools support all of the functionality offered in relational implementations of SQL. But SQL-on-Hadoop tools are a regular component of Hadoop deployments, as companies look to get developers and data analysts with SQL skills involved in programming big data applications