Demystifying Transaction Isolation Levels and Non-Repeatable Reads

Transaction Isolation table

When designing robust database applications, understanding transaction isolation is essential for ensuring data consistency and managing concurrent operations. One particularly important phenomenon to grasp is the non-repeatable read. In this post, we will delve into the different transaction isolation levels as defined by the SQL standard, explore how they affect read phenomena, and highlight where non-repeatable reads can occur.

What Are Transaction Isolation Levels?

Transaction isolation levels determine how and when the changes made by one operation become visible to other concurrent transactions. The SQL standard defines four isolation levels:

1. Read Uncommitted

2. Read Committed

3. Repeatable Read

4. Serializable

Each level controls the visibility of data modifications from other transactions and is designed to prevent specific anomalies during concurrent access.

Key Anomalies in Concurrent Transactions

Before diving into isolation levels, let’s define some of the anomalies that can occur in a multi-transaction environment:

• Dirty Read: Occurs when a transaction reads data written by another transaction that has not yet been committed.

• Non-Repeatable Read: Happens when a transaction reads the same row twice and finds different values because another transaction has modified and committed the data in between the two reads.

• Phantom Read: Occurs when a transaction re-executes a query and finds that the set of rows satisfying the query has changed due to another committed transaction.

• Serialization Anomaly: A broader inconsistency that may arise when the overall effect of concurrent transactions does not match any serial (one-at-a-time) execution order.

Isolation Levels and Their Guarantees

Let’s explore how each isolation level manages these anomalies, with a focus on non-repeatable reads.

1. Read Uncommitted

• Description: The lowest isolation level where transactions may see uncommitted changes from other transactions.

• Anomalies Allowed: Dirty reads, non-repeatable reads, and phantom reads are possible.

• Note: In many systems (such as PostgreSQL), this level behaves identically to Read Committed due to internal architectural choices like MVCC (Multi-Version Concurrency Control).

2. Read Committed

• Description: This is the default isolation level for many databases. Each SQL statement within a transaction sees only data committed before that statement began.

• Anomalies Prevented: Dirty reads are eliminated because only committed data is visible.

• Anomalies Allowed: Non-repeatable reads and phantom reads can occur.

  • Non-Repeatable Read Example: Imagine a transaction that performs two separate SELECT queries on the same row. If another transaction modifies and commits an update between these queries, the second query may return a different value than the first.

• Implications: Read Committed is suitable for many simple operations. However, when consistent reads across multiple statements are required (such as in detailed reports or financial applications), the possibility of non-repeatable reads can be problematic.

3. Repeatable Read

• Description: A transaction sees a snapshot of the database as it was at the start of the transaction (or the first non-transactional command). This snapshot remains consistent throughout the transaction.

• Anomalies Prevented: Both dirty reads and non-repeatable reads are eliminated.

  • How? Once a row is read, its state is "fixed" for the duration of the transaction, regardless of concurrent modifications.

• Anomalies Allowed: Phantom reads can occur in some systems, though PostgreSQL’s implementation of Repeatable Read prevents them, offering even stricter guarantees.

• Usage Consideration: This isolation level is well-suited for transactions that require a consistent view of data across multiple reads. However, it may lead to higher contention and require transaction retries in the case of conflicting concurrent updates.

4. Serializable

• Description: The strictest isolation level, where transactions are guaranteed to be serializable – meaning that the outcome of concurrently executed transactions is the same as if they were executed one at a time.

• Anomalies Prevented: All anomalies, including dirty reads, non-repeatable reads, phantom reads, and serialization anomalies are eliminated.

• Implications: While providing the highest degree of data consistency, Serializable isolation can incur additional overhead due to monitoring and locking mechanisms. Applications using this level must be prepared to handle serialization failures and potentially retry transactions.

Focus on Non-Repeatable Reads

A non-repeatable read occurs when a transaction reads the same row twice and finds different data because another transaction has modified and committed a change between the two reads. Here’s how the different isolation levels handle this phenomenon:

• Read Committed:

  • Behavior: Since each SQL statement starts with a fresh snapshot of committed data, a subsequent SELECT within the same transaction can see the updated data if another transaction commits a change in the interim. This means that non-repeatable reads are possible.

• Repeatable Read and Serializable:

  • Behavior: Both these isolation levels ensure that once a transaction begins, it works with a consistent snapshot of the data. Any changes committed by concurrent transactions after the initial read are not visible, thereby preventing non-repeatable reads.

When to Choose a Specific Isolation Level

• Performance vs. Consistency:

  • Read Committed offers a good balance for many everyday applications where occasional non-repeatable reads do not result in critical issues.

  • Repeatable Read or Serializable should be chosen for scenarios requiring strict consistency, such as financial transactions or complex reporting, even if this might result in a performance trade-off.

• Application Logic Considerations:

  • If your application logic can tolerate slight inconsistencies between reads (or can handle re-checking data), Read Committed may be sufficient.

  • In cases where every read must return identical data throughout the transaction, opt for Repeatable Read or Serializable to eliminate non-repeatable reads.

Practical Takeaways

• Non-repeatable reads are a common occurrence under the Read Committed isolation level.

• For operations requiring strict consistency across multiple reads, consider using Repeatable Read or Serializable isolation levels.

• PostgreSQL Note: PostgreSQL’s implementation maps Read Uncommitted to Read Committed, simplifying the choices but reinforcing the fact that non-repeatable reads are a characteristic of the Read Committed level.

For more in-depth details, you might want to review the PostgreSQL documentation on Transaction Isolation.

By understanding these nuances, developers can make informed decisions about which transaction isolation level best suits their application's needs, ensuring the right balance between performance and data integrity.

Happy coding, and may your transactions always be consistent!