- Optimization: Triggers operate close to the data, leveraging database optimizations by vendors or the open-source community. This allows for writing efficient triggers tailored to the database system’s specific capabilities.
- Data Integrity: A key advantage is maintaining data integrity. We won’t lose deletes or updates. Implementing this through triggers ensures consistency across all applications that manipulate the data instead of scattering the logic across various application codebases.
- Complexity in Handling Row Counts: Triggers must always check the
@@ROWCOUNTvariable as the first implementation statement. This is crucial because triggers can fire even when no update or insert exists (e.g., where 1=2 conditions).
- Nested Trigger Issues: When triggers cause other triggers to fire, managing row counts becomes complex. It’s often suggested to turn row counting off in such cases.
- Delete Operations in Merge Statements: Special attention is needed when dealing with delete operations in merge statements. The
@@ROWCOUNTin merge operations represents the total number of rows affected, not the count for individual insert, update, or delete actions within the trigger.
- Error Handling: Implementing robust error handling within triggers, such as using TRY-CATCH blocks, is essential to prevent triggers from blocking inserts or causing unintended side effects. This requires careful construction of queries and validation of data.
In essence, while triggers offer advantages in terms of optimization and data integrity, they also come with their complexities, especially regarding row count management, nested trigger interactions, handling exceptional cases like merge statements, and ensuring robust error handling.
- For the advantages and general information about writing triggers:
- For the disadvantages and specific implementation concerns:
Other solutions are Change Data Capture or reading date timestamps like