When working with datasets, what is data concurrency, and how is it managed?
- Data concurrency refers to multiple users accessing and potentially modifying the same data simultaneously. It is managed using techniques such as optimistic concurrency and pessimistic concurrency.
- Data concurrency refers to the ability to rollback changes made to the dataset. It is managed using rollback transactions.
- Data concurrency refers to the ability to work with data from multiple datasets concurrently. It is managed using transactions.
- Data concurrency refers to the synchronization of data between the dataset and the database. It is managed using data synchronization mechanisms.
Data concurrency refers to multiple users accessing and potentially modifying the same data simultaneously. In ADO.NET, data concurrency is typically managed using techniques such as optimistic concurrency and pessimistic concurrency. Optimistic concurrency involves checking for conflicts at the time of updating data, while pessimistic concurrency involves locking data to prevent other users from modifying it until the operation is complete. These techniques help ensure data integrity in multi-user environments.
Loading...
Related Quiz
- In Entity Framework, what is the difference between Table Splitting and Entity Splitting when it comes to mapping entities to tables?
- What is an anonymous type in LINQ, and how is it used?
- In ADO.NET, what is the difference between a DataView and a DataTable?
- What are the advantages of using connection pooling in ADO.NET?
- What is the primary purpose of a DataTable in ADO.NET?