"SQL, a powerful language for databases, lets you ask questions of your data and unlock hidden insights, no matter your technical background. With just a few basic SQL commands, you can transform raw data into meaningful information to guide decisions and fuel your projects."- Gemini 2024

In SQL (Structured Query Language), DDL and DML are two essential categories of commands used to interact with databases. DDL defines the structure of a database, and DML is used to manipulate its content.

• Purpose: Defines the structure of a database.
• Functionality: Used to create, modify, and remove objects like tables, indexes, views, and schemas.
• Examples:
  • CREATE TABLE: Creates a new table with specified columns and data types.
  • ALTER TABLE: Modifies the structure of an existing table (adding/removing columns, changing data types).
  • DROP TABLE: Removes a table from the database.
  • CREATE INDEX: Creates an index on a table column for faster retrieval.
  • CREATE VIEW: Creates a virtual table based on a query, providing a custom way to access data.

• Purpose: Manipulates data within the database.
• Functionality: Used to insert, retrieve, update, and delete data from tables. Known as CRUD for create, read, update, delete.
• Examples:
  • INSERT: Inserts new rows of data into a table.
  • SELECT: Retrieves data from one or more tables based on specific criteria.
  • UPDATE: Modifies existing data in a table based on certain conditions.
  • DELETE: Removes rows of data from a table based on conditions.

SQL (Structured Query Language) reigns supreme as the undisputed king of relational databases. It provides a universal language for interacting with these structured data stores, allowing you to retrieve, manipulate, and analyze information with ease. While the core functionalities remain consistent across SQL dialects, there are variations for specific needs. Popular examples include:

• MySQL: A widely used open-source relational database management system.
• PostgreSQL: A powerful open-source object-relational database management system.
• Presto: A distributed SQL query engine known for its speed and scalability, often used with cloud services like AWS Athena, Google BigQuery, and Databricks.

With SQL we can extract data from relational databases and turn the data into information for decision making in business, and exploration in scientific research.

-- Selecting all fields in all records in a table
select * from Orders;

-- Selecting some fields from all records in a table
select first_name, age from Customers;

-- Selecting a subset of records
select item from Orders where customer_id = 3;
select shipping_id from Shippings where status == "Pending";

-- Sorting the output
select * from Customers order by "last_name";

-- Getting distinct (unique) values in a field
select distinct "item" from Orders;

-- Selecting based on different conditions
select age from Customers where country == "USA";
select age from Customers where country != "USA";
select age from Customers where country in ("UK", "UAE");

select item from Orders where amount > 500;
select item from Orders where amount between 300 and 400;

-- Selecting based on multiple conditions with boolean expressions
select customer_id from Customers where country == "USA" and age > 30;
select customer_id from Customers where country == "USA" or age < 25;
select customer_id from Customers where country == "USA" and not age < 25;