Understanding SQL Database Isolation Levels

Database isolation is a property that defines how and when the changes made by one operation become visible to other concurrent operations. Isolation is one of the ACID (Atomicity, Consistency, Isolation, Durability) properties.

There are four isolation levels in SQL databases, as defined by the SQL standard:

1. Read Uncommitted
2. Read Committed
3. Repeatable Read
4. Serializable

Let’s explore each of these levels in detail, including their pros and cons and the circumstances in which they might be used.

In order to demonstrate isolation levels, let’s consider a scenario where two transactions are operating on the same row in a table. We’ll use a simple table called Accounts with columns AccountID, Name and Balance. Let’s assume there’s an account with AccountID 1, having the name Alice and Balance 100.

Read Uncommitted

This is the lowest level of isolation. At this level, a transaction may read changes made by another transaction that has not yet been committed, leading to a phenomenon known as “dirty reads.”

First Transaction

BEGIN TRANSACTION;
UPDATE Accounts SET Balance = Balance - 10 WHERE name = 'Alice';
-- Balance is now 90

Second Transaction

-- This transaction can read the uncommitted data from Transaction 1
SELECT Balance FROM Accounts WHERE name = 'Alice';
-- Returns 90

In the above code snippets, the Second Transaction is able to read the changes made by the First Transaction before it has committed. This is a “dirty read” and is allowed in the Read Uncommitted isolation level.

Pros: This level provides the highest concurrency level and has the lowest overhead because it does not need to lock the database.

Cons: It can lead to inconsistencies in the database due to dirty reads.

Use Case: This level can be used in scenarios where performance is critical, and the application can tolerate uncommitted changes.

Read Committed

This isolation level guarantees that any data read is committed at the moment it is read. Thus, it does not allow dirty reads. The data can be changed by other transactions between individual statements within the current transaction, leading to non-repeatable reads or phantom data.

First Transaction

BEGIN TRANSACTION;
UPDATE Accounts SET Balance = Balance - 10 WHERE name = 'Alice';

-- Balance is now 90

Second Transaction

-- This transaction will wait until Transaction 1 is committed
SELECT Balance FROM Accounts WHERE name = 'Alice';

-- Returns 100 if Transaction 1 is not committed yet

In this example, the Second Transaction only reads the changes made by the First Transaction after it has been committed, preventing dirty reads.

Pros: This level prevents dirty reads and provides a balance between data consistency and performance.

Cons: It can lead to non-repeatable reads and phantom reads, which can cause inconsistencies in the database.

Use Case: This level is suitable for applications that require data consistency but can tolerate non-repeatable reads and phantom reads.

Repeatable Read

This isolation level ensures that if a transaction reads data that is then modified by another transaction, the original transaction can’t read the new data. It will instead read the snapshot of data as it was when the transaction began. However, it can still lead to phantom reads.

First Transaction

-- Transaction 1
BEGIN TRANSACTION;
SELECT balance FROM Accounts WHERE name = 'Alice'; 

-- This creates a "snapshot" of Alice's balance

Second Transaction

-- Transaction 2
BEGIN TRANSACTION;
UPDATE Accounts SET balance = balance - 100 WHERE name = 'Alice';
COMMIT;

First Transaction Again 

-- Transaction 1
SELECT balance FROM Accounts WHERE name = 'Alice'; 
-- This will see the "snapshot" balance, not the updated balance

In this example, First Transaction reads the same data (“snapshot”) before and after the Second Transaction commits its changes, preventing non-repeatable reads.

Pros: This level prevents dirty reads and non-repeatable reads, providing a higher level of data consistency.

Cons: It can lead to phantom reads and has higher overhead due to locking.

Use Case: This level is suitable for applications that require a higher level of data consistency and can tolerate phantom reads.

Serializable

This is the highest isolation level. It provides the strictest transaction isolation. This level emulates serial transaction execution, as if transactions had been executed one after another, serially rather than concurrently.

First Transaction

-- Transaction 1
BEGIN TRANSACTION;
SELECT balance FROM Accounts WHERE name = 'Alice';

Second Transaction

-- Transaction 2
BEGIN TRANSACTION;
UPDATE Accounts SET balance = balance - 100 WHERE name = 'Alice'; 

-- This will be blocked until Transaction 1 commits

In this example, the Second Transaction cannot modify the data read by the First Transaction until the First Transaction has committed, ensuring the highest level of consistency.

Pros: This level prevents dirty reads, non-repeatable reads, and phantom reads, providing the highest level of data consistency.

Cons: It has the highest overhead due to locking and provides the lowest concurrency level.

Use Case: This level is suitable for applications that require the highest level of data consistency and can tolerate the overhead of locking.

In conclusion, the choice of isolation level depends on the specific requirements of your application. If data consistency is paramount, a higher isolation level like Serializable may be appropriate. If performance is more important, a lower isolation level like Read Uncommitted could be a better choice.

Non-Standard Database Isolation Levels

In addition to standard isolation levels,  there are non-standard isolation levels that some database providers offer. These are typically extensions or variations of the standard isolation levels, designed to provide additional flexibility or performance benefits. Here are a few examples:

1. Snapshot Isolation: This is a concurrency control method that allows transactions to work with a “snapshot” of data, representing the state of the database at the beginning of the transaction. It’s designed to provide a high level of consistency without the overhead of locks. Microsoft SQL Server and PostgreSQL are examples of DBMS that support this isolation level.

2. Read Committed Snapshot Isolation (RCSI): This is a variant of Snapshot Isolation offered by Microsoft SQL Server. It provides the benefits of Snapshot Isolation while maintaining the semantics of the Read Committed isolation level.

3. Serializable Snapshot Isolation (SSI): This is another variant of Snapshot Isolation implemented in PostgreSQL. It provides serializability, the highest level of transaction isolation, but uses a multi-version concurrency control mechanism to reduce the need for locks.

4. Cursor Stability: This is an isolation level offered by IBM DB2 and Informix. It’s similar to Read Committed but also locks the current row being accessed by a cursor, preventing other transactions from modifying it.

5. Chaos: This is a low isolation level where transactions are not isolated from each other at all. It’s not commonly used and is not supported by many DBMSs.

Remember, the choice of isolation level can significantly impact the performance and behavior of your database operations, so it’s important to understand the implications of each level and choose the one that best fits your application’s needs.

Summary of Isolation Levels