#Purpose

Rules for transaction boundaries, isolation and concurrency control.

The two failures that account for most incidents: transactions held open too long, which exhausts the connection pool and blocks vacuum, and assuming READ COMMITTED prevents anomalies it does not — the read-modify-write race that silently corrupts a balance.

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#Isolation levels and what each permits

* PostgreSQL treats READ UNCOMMITTED as READ COMMITTED. † PostgreSQL's REPEATABLE READ uses snapshot isolation and prevents phantoms, unlike the SQL standard's minimum guarantee.

The row that matters: READ COMMITTED permits lost updates. Two concurrent transactions each read a balance of 100, each subtract 30, and the result is 70 instead of 40. No error is raised.

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#The read-modify-write race

js
// BROKEN under READ COMMITTED — two concurrent runs both read the old value
const account = await tx.account.findUnique({ where: { id } });
await tx.account.update({ where: { id }, data: { balance: account.balance - 30 } });

Three correct fixes, in order of preference:

sql
-- 1. Atomic update — no read-then-write at all. Prefer this.
UPDATE accounts SET balance = balance - 30
WHERE id = $1 AND balance >= 30
RETURNING balance;

-- 2. Pessimistic lock — serialises the readers on this row
SELECT balance FROM accounts WHERE id = $1 FOR UPDATE;

-- 3. Optimistic lock — no lock held; retry on conflict
UPDATE accounts SET balance = $2, version = version + 1
WHERE id = $1 AND version = $3;      -- 0 rows affected means someone else won

Option 1 is best where the operation is expressible in SQL. FOR UPDATE costs concurrency on hot rows. Optimistic locking suits low-contention data and requires the caller to handle the retry.

Never rely on reading a value, checking it in application code, and writing it back without one of these.

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#Keep transactions short

A transaction holds locks and a connection for its entire life.

Never do these inside a transaction:

• An HTTP call to a third party. A 30-second timeout becomes a 30-second lock.
• Sending an email or publishing to a queue — if the transaction rolls back, the message has already gone. Use the outbox pattern.
• Waiting for user input.
• Processing a large file.

js
// Right: read, close, do slow work, reopen for the write
const order = await db.order.findUnique({ where: { id } });
const charge = await stripe.charges.create({ amount: order.total });   // outside

await db.$transaction(async (tx) => {
  await tx.order.update({ where: { id }, data: { chargeId: charge.id } });
  await tx.ledger.create({ data: { orderId: id, amount: order.total } });
});

Watch idle in transaction in pg_stat_activity — a non-zero steady count means transactions are open with nothing running, which is the pool exhaustion signature. Set idle_in_transaction_session_timeout so a leaked transaction cannot hold a connection indefinitely.

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#Serialisable and retries

SERIALIZABLE gives correctness without manual locking, at the cost of serialisation failures the caller must retry.

js
async function withRetry(fn, attempts = 3) {
  for (let i = 0; i < attempts; i++) {
    try {
      return await db.$transaction(fn, { isolationLevel: "Serializable" });
    } catch (e) {
      // 40001 serialization_failure, 40P01 deadlock_detected
      if (!["40001", "40P01"].includes(e.code) || i === attempts - 1) throw e;
      await sleep(Math.random() * 2 ** i * 50);      // backoff with jitter
    }
  }
}

A SERIALIZABLE transaction without retry handling is worse than READ COMMITTED — it converts a rare silent anomaly into a frequent visible error.

Deadlocks: the database detects and kills one participant. Reduce them by always acquiring locks in a consistent order (for example, always the lower account id first).

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#Boundaries and correctness

• One transaction per unit of business work — not per statement, not per request. If two writes must both succeed or both fail, they share a transaction.
• Never nest transactions expecting independent rollback. Most drivers map an inner "transaction" to a savepoint or ignore it.
• Anything with an external side effect belongs in an outbox: write the intent inside the transaction, deliver it afterwards from a worker.
• Make retried operations idempotent — a retry after an ambiguous timeout must not charge twice. Use an idempotency key.

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#Anti-patterns

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#Checklist

• Verify: The isolation level is chosen deliberately, and its anomalies are understood
• Verify: No read-modify-write happens without an atomic update or an explicit lock
• Verify: Transactions contain no HTTP calls, emails, queue publishes or user waits
• Verify: External side effects go through an outbox
• Verify: SERIALIZABLE transactions are wrapped in retry with backoff and jitter
• Verify: Locks are always acquired in a consistent order
• Verify: One transaction spans one unit of business work
• Verify: Nested transaction behaviour in the driver is known, not assumed
• Verify: idle_in_transaction_session_timeout is set
• Verify: Retryable operations carry an idempotency key
• Verify: idle in transaction connection counts are monitored

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#Anchors (restated last, read last)

The rules that must hold when you stop, repeated here because the end of the context is what you act on:

• Never rely on reading a value, checking it in application code, and writing it back without one of these.

• Never do these inside a transaction:

• The isolation level is chosen deliberately, and its anomalies are understood

• No read-modify-write happens without an atomic update or an explicit lock

• Transactions contain no HTTP calls, emails, queue publishes or user waits

• External side effects go through an outbox

• SERIALIZABLE transactions are wrapped in retry with backoff and jitter

• Locks are always acquired in a consistent order

Before reporting done, prove the module still imports — run the line for this stack and paste its output:

bash
python -c "import <package>"          # Python: the package you changed
node -e "require('./<entry>')"       # Node CJS, or: node --input-type=module -e "import './<entry>.js'"
go build ./...                        # Go