What is Isolation Level in Transactions?

Isolation Level in transaction management defines how multiple transactions interact with each other when accessing the same database data simultaneously.

In simple words:

“Isolation level controls how safely one transaction is isolated from another transaction.”

Why Isolation Levels are Needed

In real-world enterprise applications:

Thousands of users access data simultaneously
Multiple transactions run together
Concurrent updates happen frequently

Without proper isolation:

Incorrect data may appear
Duplicate updates may occur
Data inconsistency may happen

Isolation levels solve these concurrency problems.

Real-Time Banking Example

Suppose:

Account balance = ₹50,000

Two users perform transactions simultaneously:

User A withdraws ₹10,000
User B checks balance

Without isolation:

User B may see incorrect balance

Isolation levels prevent such issues.

What is Concurrency?

Concurrency means:

Multiple transactions executing at the same time

Main Problems Solved by Isolation Levels

Dirty Read
Non-Repeatable Read
Phantom Read

1. Dirty Read

Dirty read occurs when:

One transaction reads uncommitted data from another transaction

Dirty Read Example


Transaction A:
Update balance = 10000
(Not committed yet)

Transaction B:
Reads balance = 10000

Transaction A:
ROLLBACK

Problem:

Transaction B read invalid data

2. Non-Repeatable Read

Non-repeatable read occurs when:

Same query returns different values inside same transaction

Example


Transaction A:
Reads balance = 50000

Transaction B:
Updates balance = 30000
Commits

Transaction A:
Reads balance again = 30000

3. Phantom Read

Phantom read occurs when:

New rows appear during same transaction

Example


Transaction A:
SELECT * FROM employees

Transaction B:
INSERT new employee
COMMIT

Transaction A:
SELECT * FROM employees
(New row appears)

Main Isolation Levels in Spring Boot

Isolation Level	Description
READ_UNCOMMITTED	Lowest isolation level
READ_COMMITTED	Reads only committed data
REPEATABLE_READ	Prevents non-repeatable reads
SERIALIZABLE	Highest isolation level

1. READ_UNCOMMITTED

Lowest isolation level.

Transactions can:

Read uncommitted changes

Problems Allowed

Dirty reads
Non-repeatable reads
Phantom reads

Performance

Very fast, but unsafe.

Example

@Transactional(
    isolation =
    Isolation.READ_UNCOMMITTED
)

When to Use

Rarely used
Analytics systems

2. READ_COMMITTED

Most commonly used isolation level.

Transactions can:

Read only committed data

Problems Prevented

Dirty reads prevented

Problems Still Possible

Non-repeatable reads
Phantom reads

Performance

Good balance between:

Performance
Data consistency

Example

@Transactional(
    isolation =
    Isolation.READ_COMMITTED
)

Real-Time Use Case

Banking applications
Order management systems

3. REPEATABLE_READ

Ensures same row returns same value throughout transaction.

Problems Prevented

Dirty reads
Non-repeatable reads

Problems Still Possible

Phantom reads

Performance

Slower than READ_COMMITTED, but safer.

Example

@Transactional(
    isolation =
    Isolation.REPEATABLE_READ
)

Real-Time Use Case

Inventory management
Financial calculations

4. SERIALIZABLE

Highest isolation level.

Transactions execute:

One after another

Problems Prevented

Dirty reads
Non-repeatable reads
Phantom reads

Performance

Safest but slowest.

Example

@Transactional(
    isolation =
    Isolation.SERIALIZABLE
)

Real-Time Use Case

Critical banking systems
Stock trading systems

Isolation Level Comparison Table

Isolation Level	Dirty Read	Non-Repeatable Read	Phantom Read
READ_UNCOMMITTED	Possible	Possible	Possible
READ_COMMITTED	Prevented	Possible	Possible
REPEATABLE_READ	Prevented	Prevented	Possible
SERIALIZABLE	Prevented	Prevented	Prevented

How to Set Isolation Level in Spring Boot

@Transactional(
    isolation =
    Isolation.READ_COMMITTED
)
public void processPayment() {

}

Default Isolation Level

Default isolation depends on:

Database configuration

Most databases use:

READ_COMMITTED

Advantages of Isolation Levels

Maintains data consistency
Prevents concurrency issues
Improves reliability
Protects critical data

Disadvantages of Higher Isolation Levels

Reduced performance
Database locking
Deadlocks
Lower concurrency

Real-Time Example in E-Commerce Application

Product inventory management requires:

Correct stock count
Preventing overselling

Isolation levels help maintain:

Accurate inventory data

Best Practices for Isolation Levels

Use READ_COMMITTED for most applications
Use SERIALIZABLE only when necessary
Keep transactions short
Avoid unnecessary locking
Test concurrency carefully

Common Interview Questions on Isolation Levels