Optimistic locking and pessimistic locking are the two primary methods used when managing data transactions in Entity Framework (EF). Each approach offers advantages and disadvantages that might impact the system's overall performance and the way issues with data changes are handled.
To find out what optimistic and pessimistic locking mean in EF, let's investigate this realm.
Wish for the better
The foundation of optimistic locking is the notion that data conflicts are few. It let transactions to proceed while reading the data without locking it. Instead, while saving changes, it looks for conflicts.
In the event that the data has been modified by another party after it was read, an issue known as a concurrency error arises, which requires your attention to resolve. By employing something known as a concurrency token—typically a timestamp or row version—EF facilitates optimistic locking.
When storing, this token looks for conflicts by comparing the original and current values.
Benefits of optimistic locking include less strain on the database, improved performance from not having to lock and unlock all the time, more concurrent user capacity, and a decreased likelihood of deadlocks. It works well with websites where people interact with data for extended periods of time.
It's better to be safe than sorry
Conversely, pessimistic locking assumes a high frequency of data conflicts. As a result, it locks the data while it is being read to prevent simultaneous changes by others.
This prevents unauthorized users from accessing or modifying the data until the lock is lifted, which maintains it safe and consistent. However, it can slow down the database and make managing many users at once more difficult.
It is more suited for brief transactions than for websites where users interact with data for extended periods of time, and it may potentially result in deadlocks.
While pessimistic locking aims to protect data, it may make managing large numbers of users more difficult and may slow down transaction processing times as it locks data during reading, thereby leading to delays.
Last remarks
Your choice of optimistic or pessimistic locking in EF should take your application's requirements into account after assessing the advantages and disadvantages of the two locking techniques.
Pessimistic locking prioritizes data security but may make handling multiple users more difficult and may result in worse performance. Optimistic locking offers you flexibility and performance benefits but requires careful handling of concurrency issues.
When choosing an EF locking strategy, consider the type of application you are using, the frequency of data conflicts, and the significance of maintaining data consistency.
