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To prevent a client from overwriting a newer status change, make the server verify that the record is still in the version the client read. Use an HTTP version precondition such as If-Match when users may work with a record for a while and conflicts should be surfaced. Use a short database transaction with a row lock when a status transition must be serialized immediately and it is acceptable for competing requests to wait. In either case, validate and apply the transition atomically.
How lost updates happen
Suppose two clients read a ticket as pending. One changes it to approved; the other, still acting on the earlier read, changes it to rejected. If the server accepts both writes without checking that the second client’s view is current, the later write can erase the earlier one. The final value depends on which request is applied last. MDN describes this class of collision in its guide to HTTP conditional requests.
Locking strategies prevent that overwrite at different points. Optimistic locking detects that the client’s version is stale when it tries to write. Pessimistic locking prevents a competing transaction from changing the locked row until the first transaction finishes.
Optimistic locking vs. pessimistic locking
| Decision point | Optimistic version check | Pessimistic row lock |
|---|---|---|
| Where protection happens | At write time, by comparing the submitted version with the current one. | Inside a database transaction, by blocking conflicting writers or lockers while the row is locked. |
| What the competing client sees | A rejected stale update, commonly HTTP 412 Precondition Failed; the client must refresh or reconcile. |
The competing operation may wait for the lock-holding transaction to finish. |
| How long protection lasts | No database lock needs to remain open during the user’s edit session. | Only for the transaction holding the lock; keep that transaction short. |
| Main operational concerns | Stale preconditions and a clear client recovery flow. | Waiting, transaction timeouts, deadlock aborts and database isolation behavior. |
| A natural fit | Users may spend time reviewing or editing, and a collision can be explained and resolved. | A short transition must be serialized and waiting is acceptable. |
This is a behavioral comparison, not a performance benchmark. Neither method is universally faster: the right choice depends on how often operations overlap, how costly a conflict is, how long protection is needed, and what the user experience should be.
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Use an ETag and If-Match for optimistic updates
HTTP If-Match lets a client make a state-changing request conditional on the resource still matching the entity tag it received earlier. RFC 9110 identifies this pattern as a way to prevent accidental overwrites when multiple user agents act on the same resource. The server must use strong entity-tag comparison for If-Match; if the condition is false, it must not perform the requested method. A normal response for that failed precondition is 412 Precondition Failed. See RFC 9110, HTTP Semantics.
- Read the resource. Return its representation with a strong ETag, for example
"status-v17". The example is illustrative; the server defines the actual tag. - Submit the intended change with that validator. The client sends the ETag in an
If-Matchheader on the state-changing request. - Check and mutate atomically. The server compares the submitted tag with the current version and applies the transition only if they match. Do not implement this as a separate read, comparison and unguarded write that can race with another request.
- Reject a stale request without applying it. Return
412 Precondition Failedfor the failed HTTP precondition, according to the API contract. - Give the client a recovery path. Refresh the current representation, then ask the user to retry or show the current and attempted values for reconciliation.
What should a client do when an update returns 412?
A 412 means the version the request was based on is no longer current; it does not mean the requested status transition was applied. The client should fetch the latest representation and make the next action explicit. It can ask the person to try again against the new version, or show what changed alongside the attempted status so the person can decide how to proceed.
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- Do not blindly resubmit the old request with a newly fetched ETag. That would turn a stale intent into a write against newer data without resolving the conflict.
- If the refreshed state means the requested transition is already complete, handle that deliberately according to the API’s idempotency and response contract.
- Use
409 Conflict, if appropriate, for a separate domain-rule conflict; it is not a substitute for the failedIf-Matchprecondition.
RFC 9110 allows a success response in certain cases where the requested change appears already applied, but cautions against treating changes by non-cooperating agents as success too freely. Define duplicate-request behavior rather than silently discarding a status change.
Use a row lock for a short serialized transition
For a transition that should be decided against the row’s current state within one short operation, a database transaction can lock the row before validating and changing it. In PostgreSQL, SELECT ... FOR UPDATE locks selected rows against conflicting writers or lockers until the transaction ends. PostgreSQL documents this behavior in Explicit Locking.
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- Begin a transaction.
- Select and lock the target row. In PostgreSQL, use
SELECT ... FOR UPDATEfor the row being transitioned. - Check the current status and allowed transition. Make this decision using the locked row, not a stale value sent by the client.
- Update the status and commit. The transaction releases its row lock when it ends.
Keep external service calls and user interaction outside the lock-holding transaction. PostgreSQL warns that conflicting locks can wait and that applications should not hold transactions open for long periods, such as while waiting for user input. Deadlocks are also possible; PostgreSQL aborts one participant. When a transaction locks multiple records, acquire them in a consistent order where practical, and use a bounded retry policy if the operation can safely be retried. Details are in the PostgreSQL documentation on explicit locking and deadlocks.
PostgreSQL isolation-level caveat
With PostgreSQL Repeatable Read, a transaction’s snapshot can predate a lock acquired after its first query or data-modification command. PostgreSQL’s application-level consistency guidance advises using Read Committed or acquiring the needed locks before queries when explicit locks are being relied on for consistency. See Data Consistency Checks at the Application Level. This is PostgreSQL-specific guidance; other databases have their own lock and isolation semantics.
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Model status changes as transitions, not blind assignments
A status is usually part of a workflow, not just a field to overwrite. Express the requested operation as a transition such as pending → approved, then have the server validate that the current status still permits it. The version check or row lock protects the read-and-change operation from racing; the transition rule protects the workflow from an invalid change.
Make the version check and mutation atomic at the server/database boundary. A client-side check alone cannot prevent another request from changing the row between the check and the write. Also decide how a repeated request should behave: it may already have succeeded, or it may conflict with the current state, depending on the operation and API contract.
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Choosing a strategy for your API
- Choose optimistic checks when a person may read, review or edit for a while before submitting, and a conflict can be returned for deliberate recovery. It avoids holding a database lock for the duration of that interaction.
- Choose a pessimistic row lock when the transition must be serialized inside a brief transaction and the application can tolerate a competing request waiting.
- Evaluate the real workload when throughput or latency is decisive. Consider overlap frequency, conflict cost, transaction duration, waiting behavior and the client’s recovery experience; the cited documentation establishes no universal performance winner or crossover threshold.
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