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Why a shared-record save conflicts
Suppose an account manager reads a client record with an address of 10 Oak Street. Before that manager saves a phone-number change, a colleague corrects the address and saves the record. The first manager’s copy is now stale. Saving it without a concurrency check could replace the colleague’s newer record with an older snapshot.
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CAS prevents that lost update by making a write conditional on the version the editor actually read. The token represents an observed version or state; it is not itself a merge instruction. Couchbase documents that each document modification changes its CAS value, and a mutation can be conditioned on the previously observed value (Couchbase: Concurrent Document Mutations).
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- Read the record. Get the client data and its concurrency token together. With HTTP conditional requests, a server may return an ETag with the representation.
- Keep the token with that exact snapshot. Do not pair a newer record with an older token, or vice versa.
- Condition the update. For an HTTP API that supports this pattern, send the received ETag in the
If-Matchheader with the update. A database or SDK may instead use a CAS value, version column, or equivalent API. - Handle a failed condition as a conflict. The write was not accepted under the version condition, so fetch the current record and token before deciding what to do next.
RFC 9110 describes If-Match as a condition commonly used on state-changing requests to prevent accidental overwrites when multiple user agents act in parallel. The server evaluates the condition before performing the method and uses strong entity-tag comparison (RFC 9110, HTTP Semantics).
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What a failed condition means
A failed precondition means the version used for the write no longer matches the resource’s current version. In the SAP NetWeaver 750 conditional-handling documentation, a stale ETag can produce 412 Precondition Failed; a missing required If-Match can produce 428 Precondition Required (SAP Help Portal: Conditional Handling).
Those codes are examples, not a promise that every client-management API behaves identically. Check the API contract for its required headers, token format, and conflict response. ETags, database version columns, and Couchbase CAS all support version checking, but their formats and APIs are not interchangeable.
Recover without losing either person’s work
- Fetch the current record and its new token. Do not reuse the stale snapshot as the basis for a whole-record replacement.
- Compare the current values with the user’s intended changes. Identify which fields changed since the original read, including fields related by business rules.
- Retry only if the intent is still valid. For example, a phone-number change may remain valid after a colleague edits an unrelated note. Apply the intended change to the fresh record and submit it using the fresh token.
- Merge deliberately or ask for a decision. If both editors changed the same field, or changes to separate fields interact, apply a documented domain rule or show the user the current and proposed values.
Azure Cosmos DB and PlayFab document rereading current state/version information and retrying after concurrency conflicts (Azure Cosmos DB: Optimistic Concurrency Control; PlayFab: ETags and Concurrency Control). EF Core describes requerying, merging, or asking the user to resolve the changes (EF Core: Handling Concurrency Conflicts). AWS AppSync states: “The client is then expected to handle this conflict locally and retry the mutation with the updated version of the item” (AWS AppSync: Conflict Detection and Resolution).
Choose a recovery based on the edit
| Situation | Safer response | Why |
|---|---|---|
| The edit is still valid against the latest record and does not overwrite newer values. | Reapply the intended change to the fresh record and retry with its current token. | A fresh conditional write preserves the version check while allowing a still-valid edit. |
| Different fields changed, but the fields are linked by a business rule. | Merge only after checking the rule across the combined state. | Separate fields are not necessarily independent; for example, a billing address and tax jurisdiction may need to remain consistent. |
| Both users changed the same field, or the correct value depends on context. | Present the current and proposed values and let the user choose, or follow an explicit domain policy. | A version token detects change but cannot determine whose value is correct. |
| The operation is not safely repeatable or its effect is uncertain. | Reconcile the operation’s result before retrying; do not blindly repeat it. | Retrying an edit that triggers side effects may duplicate or misapply those effects. |
Why automatic merge rules need field meaning
A merge policy can be technically consistent and still be wrong for client data. AWS AppSync’s documented Automerge behavior keeps the existing server value when scalar values conflict and concatenates list values, retaining duplicates. That may suit some fields and fail for others: concatenating a list of contact methods could duplicate entries, while keeping a server scalar may discard an intentional correction. Define and test rules for each field type and business meaning rather than assuming that a generic merge preserves intent.
Quick Recap
Best Value
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Implementation checks
- Store the record snapshot and its token as one unit, and replace both after every successful read or write.
- Bound retries in application logic. Repeated conflicts should lead to a clear resolution path, not an endless retry loop.
- Distinguish a concurrency conflict from validation, authentication, authorization, and server errors; they require different remedies.
- Test simultaneous edits to the same field, unrelated fields, and related fields, plus any automatic merge rules.
- Use the status codes, token names, and retry semantics defined by the specific service rather than assuming another platform’s contract applies.
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