When many people attempt to modify data in a database at the same time, a system of controls must be implemented so that modifications made by one person do not adversely affect those of another person. This is called concurrency control.
Concurrency control theory has two classifications for the methods of instituting concurrency control:
- Pessimistic concurrency controlA system of locks prevents users from modifying data in a way that affects other users. After a user performs an action that causes a lock to be applied, other users cannot perform actions that would conflict with the lock until the owner releases it. This is called pessimistic control because it is mainly used in environments where there is high contention for data, where the cost of protecting data with locks is less than the cost of rolling back transactions if concurrency conflicts occur.
- Optimistic concurrency controlIn optimistic concurrency control, users do not lock data when they read it. When a user updates data, the system checks to see if another user changed the data after it was read. If another user updated the data, an error is raised. Typically, the user receiving the error rolls back the transaction and starts over. This is called optimistic because it is mainly used in environments where there is low contention for data, and where the cost of occasionally rolling back a transaction is lower than the cost of locking data when read.
Microsoft SQL Server supports a range of concurrency control. Users specify the type of concurrency control by selecting transaction isolation levels for connections or concurrency options on cursors. These attributes can be defined using Transact-SQL statements, or through the properties and attributes of database application programming interfaces (APIs) such as ADO, ADO.NET, OLE DB, and ODBC.
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