How to Choose the Right PostgreSQL Isolation Level and Avoid Concurrency Bugs

Why Transaction Isolation Matters

When multiple transactions run concurrently, inconsistencies such as dirty reads, non‑repeatable reads, and phantom reads can appear. Isolation levels define how a transaction sees changes made by others, balancing performance with data correctness.

Three Common Concurrency Anomalies

Dirty Read

Phenomenon: Transaction A reads data modified by Transaction B before B commits.

Example: A sees a balance of 150 ¥ after B adds 100 ¥ but hasn't committed; B rolls back, leaving A with a non‑existent balance.

Non‑Repeatable Read

Phenomenon: The same query in one transaction returns different results because another transaction modified and committed the data in between.

Example: Transaction A reads 100 ¥, Transaction B deducts 50 ¥ and commits, then A reads 50 ¥.

Phantom Read

Phenomenon: Two identical queries in a transaction return a different number of rows because another transaction inserted or deleted rows that satisfy the condition.

Example: A counts employees under 30 as 10; B inserts a new 25‑year‑old employee and commits; A counts again and gets 11.

PostgreSQL Isolation Levels

SQL defines four isolation levels; PostgreSQL implements them with some nuances.

READ UNCOMMITTED

Definition: Allows reading uncommitted changes (dirty reads).

PostgreSQL behavior: Dirty reads are impossible; the level degrades to READ COMMITTED because of MVCC.

Set command:

READ COMMITTED (default)

Definition: A transaction sees only data committed by other transactions.

Prevents: Dirty reads.

Does not prevent: Non‑repeatable reads and phantom reads.

How it works: Each SELECT obtains a fresh snapshot.

Set command:

Typical use: Most OLTP workloads.

REPEATABLE READ

Definition: Guarantees that repeated reads of the same query within a transaction return identical results.

Prevents: Dirty reads and non‑repeatable reads; in PostgreSQL it also prevents phantom reads via snapshot isolation.

How it works: A snapshot is taken at transaction start; all queries use that snapshot.

Set command:

Potential issue: Write conflicts may cause serialization failures, requiring retries.

Typical use: Reporting, complex analytics.

SERIALIZABLE

Definition: The strictest level; results are equivalent to executing transactions serially.

Prevents: All three anomalies.

How it works: Uses snapshot plus conflict detection; if consistency cannot be guaranteed, the transaction aborts.

Set command:

Application requirement: Must implement retry logic for aborted transactions.

Typical use: Banking, payments, flash‑sale systems where consistency is non‑negotiable.

Practical Usage

Setting Isolation Inside a Transaction

BEGIN;
SET TRANSACTION ISOLATION LEVEL REPEATABLE READ;
SELECT * FROM accounts WHERE user_id = 1;
UPDATE accounts SET balance = balance - 100 WHERE user_id = 1;
COMMIT;

Changing the Default for a Database

ALTER DATABASE your_db_name SET default_transaction_isolation = 'repeatable read';

Viewing the Current Level

SHOW transaction_isolation;

Production Tips

Long‑running transactions: In REPEATABLE READ or SERIALIZABLE they can cause old row versions to accumulate; break work into smaller batches.

Implicit transactions: Some drivers (e.g., JDBC with autoCommit=false) may start a transaction without you noticing; explicitly use BEGIN … COMMIT.

Retry logic: SERIALIZABLE transactions may abort with “could not serialize access …”; wrap them in a retry loop.

Isolation vs. locks: Isolation ensures consistency, while explicit locks (e.g., SELECT … FOR UPDATE) protect business rules.

Read‑only transactions: Use BEGIN TRANSACTION READ ONLY ISOLATION LEVEL REPEATABLE READ; to skip write checks and improve performance.

Choosing a level: OLTP → READ COMMITTED; OLAP/reporting → REPEATABLE READ; financial core → SERIALIZABLE with retries.

Recommendation Summary

For most applications, READ COMMITTED offers the best balance of performance and consistency. Use REPEATABLE READ when a stable snapshot is required, such as for reports. Reserve SERIALIZABLE for scenarios that cannot tolerate any inconsistency, and be prepared to implement transaction retries.