Optimistic update
An optimistic update presents an expected change in client-side state before the corresponding operation is confirmed, then reconciles or reverses the change if needed.
Latency
An optimistic update is a client-side update applied before confirmation that the corresponding operation will succeed or be accepted by the authoritative system.
- How it is used
- Hides user-perceived write latency by showing client-side state changes before background synchronization completes.
- How deep it goes
- Explains shadow writes, asynchronous synchronization, conflict strategies, consistency guarantees, and retries without prescribing a single synchronization protocol.
- Examples
- Uses an e-commerce shopping cart and a task table merged with a shadow write queue.
- What you can do after
- Evaluate/understand when immediate local feedback justifies reconciliation, stale reads, and synchronization-error handling.
React in Depth
An optimistic update is a technique that changes locally cached data before a server mutation is confirmed, then reconciles it with the server result.
- How it is used
- Improves remote-data user experience by making mutations appear immediate while server confirmation is pending.
- How deep it goes
- Explains cache updates, snapshots, rollback, server reconciliation, and TanStack Query callbacks, but not conflict resolution.
- Examples
- Uses a goal-tracking list, temporary identifiers, the useAddThing hook, and the better-reactive example.
- What you can do after
- Apply optimistic mutations with TanStack Query, including cache snapshots, rollback handling, and server-result replacement.
Related concepts
- cachinguses · Caching is the practice of storing reusable data or computation results so subsequent access can avoid repeating the original retrieval or computation.
- read-your-writesaddresses · Read-your-writes consistency is a guarantee that subsequent reads reflect a client’s or session’s successfully completed writes.
- meanaddresses · A mean is a measure of central tendency, calculated as the arithmetic average of values or, for a random variable, as the probability-weighted average of its possible values.
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