Azure Table Storage handles concurrency using optimistic concurrency control with ETags. When an entity is read, its ETag value is also retrieved. Upon updating or deleting the entity, the client must provide the original ETag. If it matches the current ETag in storage, the operation proceeds; otherwise, a conflict occurs.
To manage concurrent access to table data, employ these strategies:
1. Retry policy: Implement exponential backoff for retries when conflicts occur, reducing contention and improving overall performance.
2. Merge updates: Instead of replacing entire entities, merge changes by updating specific properties, minimizing conflicts.
3. Batch operations: Group multiple operations into a single batch transaction, ensuring atomicity and reducing round-trips.
4. Partitioning: Distribute data across multiple partitions, allowing parallelism and increasing throughput.
5. Caching: Cache frequently accessed data, reducing load on Table Storage and avoiding unnecessary conflicts.
6. Optimistic locking: Use ETags for optimistic locking, detecting conflicts early and resolving them as needed.
