Optimistic Locking is a strategy where you read a record, take note of a version number (other methods to do this involve dates, timestamps or checksums/hashes) and check that the version hasn’t changed before you write the record back. When you write the record back you filter the update on the version to make sure it’s atomic. (i.e. hasn’t been updated between when you check the version and write the record to the disk) and update the version in one hit.
If the record is dirty (i.e. different version to yours) you abort the transaction and the user can re-start it.
This strategy is most applicable to high-volume systems and three-tier architectures where you do not necessarily maintain a connection to the database for your session. In this situation the client cannot actually maintain database locks as the connections are taken from a pool and you may not be using the same connection from one access to the next.
Pessimistic Locking is when you lock the record for your exclusive use until you have finished with it. It has much better integrity than optimistic locking but requires you to be careful with your application design to avoid Deadlocks. To use pessimistic locking you need either a direct connection to the database (as would typically be the case in a two tier client server application) or an externally available transaction ID that can be used independently of the connection.
In the latter case you open the transaction with the TxID and then reconnect using that ID. The DBMS maintains the locks and allows you to pick the session back up through the TxID. This is how distributed transactions using two-phase commit protocols (such as XA or COM+ Transactions) work
Transactional isolation is usually implemented by locking whatever is accessed in a transaction. There are two different approaches to transactional locking: Pessimistic locking and optimistic locking.
The disadvantage of pessimistic locking is that a resource is locked from the time it is first accessed in a transaction until the transaction is finished, making it inaccessible to other transactions during that time. If most transactions simply look at the resource and never change it, an exclusive lock may be overkill as it may cause lock contention, and optimistic locking may be a better approach. With pessimistic locking, locks are applied in a fail-safe way. In the banking application example, an account is locked as soon as it is accessed in a transaction. Attempts to use the account in other transactions while it is locked will either result in the other process being delayed until the account lock is released, or that the process transaction will be rolled back. The lock exists until the transaction has either been committed or rolled back.
With optimistic locking, a resource is not actually locked when it is first is accessed by a transaction. Instead, the state of the resource at the time when it would have been locked with the pessimistic locking approach is saved. Other transactions are able to concurrently access to the resource and the possibility of conflicting changes is possible. At commit time, when the resource is about to be updated in persistent storage, the state of the resource is read from storage again and compared to the state that was saved when the resource was first accessed in the transaction. If the two states differ, a conflicting update was made, and the transaction will be rolled back.
In the banking application example, the amount of an account is saved when the account is first accessed in a transaction. If the transaction changes the account amount, the amount is read from the store again just before the amount is about to be updated. If the amount has changed since the transaction began, the transaction will fail itself, otherwise the new amount is written to persistent storage.