PostgreSQL Isolation Levels Explained

PostgreSQL's transaction isolation levels are crucial for controlling the visibility of changes made by one transaction to other concurrent transactions, affecting both data integrity and concurrency. Here are the isolation levels explained in bullet points:

• Read Uncommitted:

  • This level is not explicitly supported by PostgreSQL; instead, the behavior of Read Uncommitted is treated as Read Committed in PostgreSQL. It's mentioned for SQL standard compliance.

  • Transactions can only see changes committed before the transaction began, preventing dirty reads.

• Read Committed (Default level in PostgreSQL):

  • Each query within a transaction sees only data committed before the query (not the transaction) started.

  • Prevents dirty reads but allows non-repeatable reads and phantom reads, where the result of a query can change if rerun within the same transaction due to other committed transactions.

• Repeatable Read:

  • All queries in a transaction see a snapshot of data as it was at the start of the transaction, preventing non-repeatable reads.

  • Guarantees that if a row is read twice in a transaction, the same values are returned each time, but other transactions can insert new rows that match the queries.

  • In PostgreSQL, this level also effectively prevents phantom reads due to its implementation using serialization snapshots.

• Serializable:

  • Provides the strictest level of isolation by ensuring that transactions execute with the same effects as if they were executed sequentially, one after the other, rather than concurrently.

  • Ensures no dirty reads, non-repeatable reads, or phantom reads occur, providing complete isolation from other transactions.

  • Achieved in PostgreSQL through predicate locking, which might lead to increased transaction rollbacks in highly concurrent systems due to serialization conflicts. This level is best used when absolute consistency is required, and concurrency is lower.

Choosing the right isolation level in PostgreSQL involves balancing the need for data consistency against the performance implications of locking and the potential for transaction rollbacks. Higher isolation levels increase data integrity at the cost of potential performance degradation and increased likelihood of needing to handle transaction conflicts in your application.