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Home/ Questions/Q 3756762
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Editorial Team
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Editorial Team
Asked: May 19, 20262026-05-19T09:54:07+00:00 2026-05-19T09:54:07+00:00

I have a database with 50 tables and I want to log users requests,

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I have a database with 50 tables and I want to log users requests, such as inserts, updates or deletes on all the tables in the database. I can also create a trigger for this for each request type.

What is the best way to do this from a performance perspective or is there a better way to track this?

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  1. Editorial Team
    Editorial Team
    2026-05-19T09:54:07+00:00Added an answer on May 19, 2026 at 9:54 am

    You can also create audit tables which are populated by triggers (and which allow much more flexibility than change data capture). The critical component is to capture sets of data not try to work row-by-row. It does add some overhead yes, but if you write the triggers correctly, it isn’t that much. Be sure to capture who (including which application if you have multiple applications hitting the database) and when as well as the old and new values. Set up one audit table per table you want audited (too much locking if you use only one audit table). And at the time you set up your system, write the code to get data back from a bad transaction or set of transactions. That makes it easier to recover when you do have something go wrong and you need to revert. We use two tables per table audited, one contains the info about the process that did the changes (name of the application, date, user, etc. and an auditid), the other contains the details about what was changed (old and new values, ID of the record being affected and column affected). Our structure enables us to use the same structure for each table being audited, and allows the tables to change without having to change the audit table and allows us to easily script the audit tables for a new tables. It is also easy for us to see what records were changed at the same time or in the same process or to find out which of the many applications which touch our database was responsible for the bad data as well as telling us who in particular was responsible for the bad data. This helps us track down application bugs and find out why the data was changed the way it was in some cases. It also makes it easier for us to track down all the data that was affected by a broken process rather than just the one we knew about.

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