Isolation Level (Database)

Isolation Level is a property in database transaction management that defines the extent to which transactions are isolated from each other. It determines how and when changes made by one transaction are visible to other concurrent transactions, affecting the trade-off between consistency and concurrency.

Key Concepts

• Transaction Isolation: Ensures that concurrent transactions do not interfere with each other inappropriately.
• Anomalies: Lower isolation levels can lead to issues like dirty reads, non-repeatable reads, and phantom reads.
• Trade-offs: Higher isolation levels improve consistency but may reduce performance due to increased locking and reduced concurrency.

Types of Isolation Levels

The SQL standard defines four primary isolation levels:

Isolation Level	Description	Prevented Anomalies	Allowed Anomalies
Read Uncommitted	Transactions can read uncommitted changes made by other transactions.	None	Dirty Reads, Non-Repeatable Reads, Phantom Reads
Read Committed	Transactions can only read committed data.	Dirty Reads	Non-Repeatable Reads, Phantom Reads
Repeatable Read	Ensures consistent reads for data accessed multiple times within a transaction.	Dirty Reads, Non-Repeatable Reads	Phantom Reads
Serializable	Provides the highest level of isolation by ensuring that transactions appear to execute serially.	Dirty Reads, Non-Repeatable Reads, Phantom Reads	None

Explanation of Anomalies

• Dirty Reads: A transaction reads data modified by another transaction that has not yet committed.
• Non-Repeatable Reads: A transaction reads the same data twice and gets different results due to modifications by another transaction.
• Phantom Reads: A transaction reads a set of rows based on a condition, and another transaction inserts or deletes rows that meet the condition.

Examples

Read Uncommitted Example

-- Transaction A
BEGIN TRANSACTION;
UPDATE accounts SET balance = 500 WHERE account_id = 1;

-- Transaction B
SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED;
SELECT balance FROM accounts WHERE account_id = 1; -- Reads uncommitted balance of 500.

-- Transaction A
ROLLBACK; -- Balance reverts, but Transaction B already used dirty data.

Repeatable Read Example

-- Transaction A
BEGIN TRANSACTION;
SELECT balance FROM accounts WHERE account_id = 1; -- Reads balance as 1000.

-- Transaction B
BEGIN TRANSACTION;
UPDATE accounts SET balance = 800 WHERE account_id = 1;
COMMIT;

-- Transaction A
SELECT balance FROM accounts WHERE account_id = 1; -- Still reads balance as 1000 due to Repeatable Read.
COMMIT;

Serializable Example

-- Transaction A
BEGIN TRANSACTION;
SELECT COUNT(*) FROM orders WHERE status = 'pending';

-- Transaction B
BEGIN TRANSACTION;
INSERT INTO orders (order_id, status) VALUES (123, 'pending');
-- Blocked until Transaction A completes to ensure serializability.

Trade-offs

The following table summarizes the trade-offs for each isolation level:

Isolation Level	Performance Impact	Use Case
Read Uncommitted	Highest concurrency	Non-critical applications or logging systems
Read Committed	Balanced	General-purpose transaction management
Repeatable Read	Moderate performance loss	Financial systems requiring consistent reads
Serializable	Highest consistency	Critical systems with strict data integrity

Applications

• Banking Systems: Use Repeatable Read or Serializable for financial transactions to avoid inconsistencies.
• E-Commerce: Often use Read Committed for balancing performance and consistency.
• Analytics Systems: May use Read Uncommitted for faster data ingestion and processing.

See Also

• Transaction Management
• Dirty Read
• Non-Repeatable Read
• Phantom Read
• Concurrency Control
• Database Anomalies