Appending large datasets: Magic ETL vs Redshift

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Appending large datasets: Magic ETL vs Redshift

Hi,

 

I have a need to append large datasets together with Domo, (Google analytics data in Big Query).

 

According to the documentation when you have inputs larger than 100m rows you should use Redshift to transform the data.

https://knowledge.domo.com/Training/Self-Service_Training/Best_Practices_Resource_Guide/Data_Process...

 

I compared doing large dataset appends in Magic ETL against Redshift and they both took a similar amount of time to complete. I was wondering what is the rationale behind the recommendation to use redshift when there doesn't seem to be an improvement in performance?

 

 

domo_redshift_test.PNG

 

 

 

 

 

 

 

 

 

domo_etl_test.PNG

 

 

 

 

 

 

 

 

 

Thanks

White Belt

Re: Appending large datasets: Magic ETL vs Redshift

Are you only appending these two datasets, or are you doing more calculations? If you only want to append them, you may want to consider using DataFusion since that's specifically designed for simple joins/appends on very large datasets.

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