Database isolation levels define how transactions interact with each other in a database, particularly when multiple transactions are executed concurrently. These levels control the visibility of changes made by one transaction to other transactions before the first transaction is committed. Isolation levels are crucial for maintaining data consistency and integrity. In this article, we'll explore four primary isolation levels defined by the SQL standard - Read Uncommitted, Read Committed, Repeatable Read, and Serializable - and provide examples of how they affect transaction behavior.
1. Read Uncommitted
1.1 Definition
At this level, a transaction can read data that has been modified by other transactions but not yet committed. This is the least restrictive isolation level and allows for the highest level of concurrency.
1.2 Issues
Dirty Reads: Transactions can read uncommitted changes from other transactions, which may later be rolled back.
Example:
- Transaction A: Updates the price of a product but hasn’t committed.
- Transaction B: Reads the new price before Transaction A commits.
- If Transaction A rolls back, Transaction B has acted on incorrect data.
1.3 Use Case
Rarely used in practice due to the risk of reading invalid data, but may be used when performance is prioritized over consistency.
2. Read Committed
2.1 Definition
A transaction can only read data that has been committed by other transactions. However, other transactions can modify data after it has been read, meaning that data may change between different reads within the same transaction.
2.2 Issues
Non-Repeatable Reads: A transaction might get different results if it reads the same data multiple times because other transactions may commit changes in between.
Example:
- Transaction A: Reads a product price.
- Transaction B: Updates and commits the price.
- Transaction A: Reads the price again, but it’s different from the first read.
2.3 Use Case
This is the default isolation level in many databases (e.g., PostgreSQL, Oracle) and is a good balance between consistency and concurrency.
3. Repeatable Read
3.1 Definition
A transaction can read only committed data, and once a transaction reads data, other transactions cannot modify that data until the first transaction completes. This ensures that if a transaction reads the same data multiple times, it will get the same result.
3.2 Issues
Phantom Reads: New rows inserted by other transactions may appear if the transaction executes a query that returns a range of rows (e.g., using WHERE), but rows themselves cannot be modified.
Example:
- Transaction A: Reads all orders from a customer.
- Transaction B: Adds a new order and commits.
- Transaction A: Re-reads the orders, and the new order appears.
3.3 Use Case
Useful when transactions need to ensure that data does not change between multiple reads, ensuring more consistent reads.
4. Serializable
4.1 Definition
This is the strictest isolation level, ensuring complete isolation between transactions. Transactions are executed in such a way that they appear to be executed serially, one after the other, even though they may be executed concurrently.
4.2 Issues
None: Prevents all anomalies such as dirty reads, non-repeatable reads, and phantom reads.
Example:
- Transaction A: Reads all inventory items.
- Transaction B: Tries to add a new inventory item but is blocked until Transaction A completes.
4.3 Performance
This level can significantly reduce performance due to the need for locks or serialization mechanisms, leading to more transaction conflicts.
4.4 Use Case
Used when data integrity is critical and no anomalies can be tolerated, but it can severely limit concurrency.
Summary
Understanding these isolation levels helps you choose the right balance between performance and consistency in database transactions. Lower levels like Read Uncommitted are faster but risk inconsistency, while higher levels like Serializable ensure data integrity at the cost of slower performance.
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