When it comes to join two or more data sets, ETL developers are in dilemma whether to choose source qualifier (SQ) or joiner transformation.
I have collated a few differences between these two Informatica transformations. It will help you in deciding whether to use a source qualifier or joiner in your business requirements.
Source Qualifier Transformation vs Joiner Transformation
Let’s compare both transformations in tabular form.
|Source Qualifier (SQ) Transformation
|The performance of source qualifier transformation is better and optimized than joiner transformation.
|The performance of the joiner transformation is slower compared to the source qualifier transformation.
|The source qualifier transformation is used to join two or more homogeneous sources.
|The joiner transformation is used to join two or more homogeneous or heterogeneous sources.
|This transformation performs logical or mathematical operations like filtering, aggregator, sorting, and many more.
|This transformation performs only join operations like inner join (or normal join), left join, right join (master outer join or detail outer join), and full outer join.
|SQ transformation does not create a cache because the query is executed on the database directly while running the job.
|The joiner transformation creates the cache for the master data set while running the job. One is the ‘index cache’ and another is the ‘data cache’.
|The source qualifier transformation supports equi and non-equi join.
|The joiner transformation supports only equi join.
This comparison of SQ and joiner transformation covered all the basic differences. Please note that both are active types of transformation.
In this Informatica series, I have covered differences of transformation articles –
- Active transformation vs Passive transformations in Informatica | with Examples
- Filter transformation vs Router transformations in Informatica
- Joiner transformation vs Lookup transformation in Informatica
If you have any queries or points to add, please comment below.
Thanks for Reading!
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