Hi Dinesh M, you may use this as a reference for some optimization checks

• If the Loop is in the Client Action, if possible, you can move the loop inside the single service action you created
• In entity action, you might want to try using (Update) only instead of (CreateOrUpdate)
• If there is a query first in your update logic, you might want to take a look at it also, you can use groupby or select only the columns needed in the logic.
• You might also check the execution time of the 3 update logics you have to verify which one causes the slowdown, and start with that info, on how you can improve your update logic
  • You can use a debugger or add a LogMessage with a time of execution to check the duration of each logic you have

Best Regards,

Philip Paolo

Hi @Dinesh Murugan,
Despite @Daniël Kuhlmann  had already specified the respective best practices to taken into consideration; Here's what something I would suggest:

1- You should re-asses your DB arch to make these types of usecases to be handle hassle free.
2- If DB arch is good enough & no refactor is needed then in that case considering the situation where you want to save the data of 3 diff packets in one call.. I would recommend you to think of handeling this with the help of timer via a custom job approach. Like sharing the entire JSON meta to server & using timer to process this. 
But again this may affect your UX ... 
https://success.outsystems.com/documentation/outsystems_developer_cloud/building_apps/use_timers/create_and_run_timers/

Good Luck

Hi @Dinesh Murugan ,

To improve execution time when processing multiple entity updates, avoid calling service actions or performing entity updates inside loops. Instead, accumulate the required changes in local data structures (e.g., lists or records) during the loop execution, and apply updates in bulk after the loop completes.

Also, minimize row-by-row database operations by using bulk update patterns where possible. This reduces database transaction overhead and improves scalability.

Additionally, ensure all necessary data is fetched once before the loop begins. Avoid repeated synchronous reads (like GetEntityById) within loops, as these can significantly degrade performance.

Thanks,

Senthil Nathan

Hi @Dinesh Murugan ,

Adding to @Daniël Kuhlmann response.

I'd suggest going straight to Advanced SQL and bypassing the "For Each" loop entirely.

The lag might be caused by the round-trips between your app and the database. Even inside one Service Action, running Entity Actions in a loop will always be slow in a cloud environment like ODC.

Since you're in ODC, you can do a set-based update using PostgreSQL’s JSON functions. This way, the database handles everything in one go.

The Workflow:

1. Use JSON Serialize to turn your list into a string.

2. Pass that string to an Advanced SQL block.

3. Use jsonb_to_recordset to join that JSON directly to your entity.

Sample SQL (ODC):

UPDATE {YourEntity} AS Target SET    [Status] = Source."Status",    [ModifiedDate] = Source."ModifiedDate" FROM    jsonb_to_recordset(@JSONInput::jsonb) AS Source(        "Id" BIGINT,        "Status" TEXT,        "ModifiedDate" TIMESTAMP    ) WHERE    Target.[Id] = Source."Id";

What the @JSONInput looks like:

[  {    "Id": 101,    "Status": "Processed",    "ModifiedDate": "2026-05-06T10:00:00Z"  }]

This usually drops execution time from seconds to milliseconds because you're only hitting the database once. 

Worth a try!