Definition
Optimistic Locking
Optimistic locking is a concurrency strategy that assumes conflicts are rare: instead of locking a record while it's being edited, it lets multiple users read freely and checks for conflicts only at write time, usually via a version number. If the version changed since you read it, your write is rejected so you can retry — preventing one user from silently overwriting another's changes.
Key takeaways
- Optimistic locking assumes conflicts are rare: it allows free concurrent reads and detects collisions only at write time, typically via a version number.
- An update is conditional — write only if the row's version still matches the one read — so a stale write affects zero rows and surfaces a conflict.
- It avoids the read-blocking of pessimistic locking, making it ideal when reads vastly outnumber conflicting writes, as in collaborative apps.
- The guarantee is no lost update: one user can never silently overwrite another's changes.
When two people edit the same record at once, the naive last-write-wins behavior silently discards one person's work. Pessimistic locking prevents this by locking the row on read, but that blocks other readers and scales poorly under contention. Optimistic locking takes the opposite bet: assume conflicts are uncommon, allow concurrent reads, and detect the rare collision at the moment of writing.
The classic mechanism is a version column. Each row carries a version number; a client reads the row and its version, and its update is conditional — write only if the version still matches what was read, incrementing it in the same statement. If another writer got there first, the version no longer matches, zero rows update, and the application surfaces a conflict for the user to merge or retry.
This trades a guaranteed lock for a possibility of retry, which is the right trade when reads vastly outnumber conflicting writes — the common case in collaborative software. It keeps the system responsive and lock-free while still guaranteeing no lost update.
Planoda uses optimistic version checks on mutable rows so concurrent edits from teammates or agents fail loudly with a conflict rather than silently overwriting each other.
Related terms
- Eventual ConsistencyEventual consistency is a guarantee in distributed systems that, if no new updates are made, all replicas of the data will converge to the same value — eventually. It accepts that reads may briefly see stale data in exchange for higher availability and lower latency, trading the strict immediacy of strong consistency for resilience and scale.
- IdempotencyIdempotency is the property that performing an operation multiple times produces the same result as performing it once. A request that charges a card or creates a record is made idempotent by attaching a unique key, so that retries from network failures or duplicate sends don't cause double charges or duplicate data — essential for reliable distributed systems.
- Row-Level Security (RLS)Row-level security (RLS) is a database feature that restricts which rows a query can read or modify based on the current user or context. Instead of relying solely on application code to filter data, the database itself enforces access policies on every query — a strong defense for multi-tenant systems where one workspace's data must never leak to another.
- Transactional OutboxThe transactional outbox is a reliability pattern that guarantees a side effect — a webhook, an event, a notification — fires exactly when its database change commits, and never otherwise. The action is written to an outbox table inside the same transaction as the data change, then a separate process delivers it, eliminating the lost or phantom events that plague naive 'save then send' code.
- Audit TrailAn audit trail is an append-only, time-ordered record of who did what, when, and to which object across a system. Every create, edit, delete, and approval is logged immutably, so any state can be traced back to the actions that produced it. Audit trails underpin accountability, debugging, compliance, and — increasingly — oversight of what AI agents do.