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🧠 What is DML?
Data Manipulation Language (DML) is a core component
of SQL used to manage data within relational databases. It includes
commands that let you:
DML commands operate on table data, not the structure
(which is handled by DDL).
🔧 1. INSERT – Adding New
Data
✅ Basic Syntax
sql
INSERT
INTO table_name (column1, column2, ...)
VALUES
(value1, value2, ...);
✅ Example
sql
INSERT
INTO Students (StudentID, Name, Age)
VALUES
(1, 'Alice', 22);
🔹 Insert Multiple Rows
sql
INSERT
INTO Students (StudentID, Name, Age)
VALUES
(2,
'Bob', 20),
(3,
'Carol', 23);
📋 Table: Students
StudentID |
Name |
Age |
1 |
Alice |
22 |
2 |
Bob |
20 |
3 |
Carol |
23 |
⚠️ Best Practices
📝 2. SELECT – Retrieving
Data
The SELECT statement is the most used SQL command to
query data.
✅ Select All Columns
sql
SELECT
* FROM Students;
✅ Select Specific Columns
sql
SELECT
Name, Age FROM Students;
✅ Filtering with WHERE
sql
SELECT
* FROM Students
WHERE
Age > 21;
✅ Sorting Results
sql
SELECT
* FROM Students
ORDER
BY Age DESC;
✅ Using Aliases
sql
SELECT
Name AS StudentName FROM Students;
📋 SELECT with Clauses
Clause |
Purpose |
WHERE |
Filter rows |
ORDER BY |
Sort result |
LIMIT |
Restrict number of
rows |
GROUP BY |
Group rows by
a column |
HAVING |
Filter grouped rows |
✅ Aggregate Functions
sql
SELECT
COUNT(*), AVG(Age)
FROM
Students;
🔄 3. UPDATE – Modifying
Data
✅ Syntax
sql
UPDATE
table_name
SET
column1 = value1, column2 = value2
WHERE
condition;
✅ Example
sql
UPDATE
Students
SET
Age = 24
WHERE
StudentID = 1;
⚠️ Important Note
Always use a WHERE clause unless you want to update all
records.
✅ Update Multiple Columns
sql
UPDATE
Students
SET
Name = 'Alice Smith', Age = 23
WHERE
StudentID = 1;
📋 Table After Update
StudentID |
Name |
Age |
1 |
Alice Smith |
23 |
2 |
Bob |
20 |
3 |
Carol |
23 |
🗑️ 4. DELETE – Removing
Data
✅ Syntax
sql
DELETE
FROM table_name
WHERE
condition;
✅ Example
sql
DELETE
FROM Students
WHERE
StudentID = 2;
⚠️ Without a WHERE clause, all
rows will be deleted.
🔁 5. DML vs DDL – Quick
Recap
Feature |
DML |
DDL |
Purpose |
Manipulate data |
Manage structure |
Affects |
Table rows |
Table
definitions |
Commands |
INSERT, UPDATE,
DELETE, SELECT |
CREATE, ALTER, DROP |
🧪 Real-World Use Case
Let’s say you’re managing an e-commerce database.
✅ Products Table
sql
CREATE
TABLE Products (
ProductID INT PRIMARY KEY,
Name VARCHAR(50),
Price DECIMAL(10, 2),
InStock INT
);
✅ Insert Data
sql
INSERT
INTO Products VALUES
(1,
'Laptop', 799.99, 5),
(2,
'Mouse', 25.00, 30),
(3,
'Keyboard', 45.00, 15);
✅ Increase Price of All Products
by 10%
sql
UPDATE
Products
SET
Price = Price * 1.10;
✅ Delete Out-of-Stock Items
sql
DELETE
FROM Products
WHERE
InStock = 0;
✅ View Expensive Products
sql
SELECT
* FROM Products
WHERE
Price > 100
ORDER
BY Price DESC;
🔍 Additional Filtering
Techniques
✅ BETWEEN
sql
SELECT
* FROM Products
WHERE
Price BETWEEN 30 AND 100;
✅ LIKE (Pattern Matching)
sql
SELECT
* FROM Products
WHERE
Name LIKE 'K%'; -- Starts with K
✅ IN
sql
SELECT
* FROM Students
WHERE
Age IN (20, 22, 23);
🔐 Transaction Support
with DML
DML statements can be wrapped in transactions for
safety.
sql
START
TRANSACTION;
UPDATE
Products
SET
Price = 0
WHERE
ProductID = 1;
ROLLBACK;
-- Undo changes
Use
COMMIT to save changes permanently.
📋 Transaction Commands
Command |
Purpose |
START TRANSACTION |
Begins transaction |
COMMIT |
Saves changes
permanently |
ROLLBACK |
Reverts all changes in
the block |
✅ Summary Table
Command |
Action |
Common Use Case |
INSERT |
Add new records |
Register users, add
products |
SELECT |
Retrieve
records |
Reporting,
filtering, dashboards |
UPDATE |
Modify existing
records |
Edit profile, change
password |
DELETE |
Remove
records |
Delete
expired data, users |
A: SQL is a query language, not a general-purpose programming language. It’s used to communicate with databases.
A: SQL is a language. MySQL is a database management system (DBMS) that uses SQL.
A: Yes. Libraries like JDBC (Java) or sqlite3/sqlalchemy (Python) allow SQL integration.
A: A JOIN combines rows from two or more tables based on a related column between them.
A: The process of structuring data to reduce redundancy and improve integrity.
A: WHERE filters rows before aggregation. HAVING filters groups after aggregation.
A: SQL keywords are case-insensitive, but string comparisons may be case-sensitive, depending on the DBMS.
A: SQL can handle moderate volumes. For large-scale datasets, use SQL-based engines like Presto, Hive, or BigQuery.
A: A view is a virtual table based on the result of a query. It doesn't store data itself.
A: Use parameterized queries or prepared statements instead of dynamic SQL strings
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