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Connector Improvement: Fivetran History Mode Tracking on Custom columns only

Not planned
Nikhil Srivastav User

Hi Team,

Query :
On another note, I've noticed that History Mode is currently tracking changes for all columns in the USER table. Can we explore the possibility of narrowing this down to specific columns, such as USER_ID and USER TYPE? Are there any options or configurations available for this within Fivetran?
Answer:
Unfortunately, this is not possible in history mode because we are tracking all the changes made to a table. This means that every update, deletion, and addition is recorded and preserved. (reference document)
 
You are more than welcome to raise a feature request for the same, and our product team will be happy to get in touch with you. 


here I am raising a feature request to cater this.

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Comments

2 comments

Date Votes
  • Official comment
    Lucas Alexander Fivetranner
    • Edited

    Hi Nikhil, Luke from the Product team here!

    Thanks for submitting this feature request. Are you submitting this request for a specific connector?

    Regardless of which connector this is for, we carefully consider any request to add configuration to Fivetran connectors. Additional configuration comes at a real cost of increased code complexity and maintenance effort. That results in fewer new connectors and features. This isn't something we are planning to add currently.

    That being said, if the use case that requires additional configuration is popular, we'll consider it. Every upvote on requests like this increases the case for adding it.

    Thanks,
    Luke

  • Bill Lyons User
    • Edited

    Please add this option! For us, this is for Salesforce source/Snowflake destination, but this same principle could apply to many potential sources and destinations. This could save potentially hundreds of thousands of MAR with some Salesforce tables, where simple fields like last_viewed_date, last_referenced_date, and others change when nothing else in the record changes. Lacking this requires building a Stream and Task in Snowflake to do this work.