I would suggest going with joins for a transactional data source to avoid duplication or wrong calculations.
Wrong details would be shown while blending due to a different level of granularity or aggregation. Data blending should be used when you don't have duplicated values in data sources and to prevent the creation of a new source from existing sources.
When to Substitute Joining for Blending
1. Data needs cleaning.
If your tables do not match up with each other correctly after a join, set up data sources for each table, make any necessary customizations (that is, rename columns, change column data types, create groups, use calculations, etc.), and then use data blending to combine the data.
2. Joins cause duplicate data.
Duplicate data after a join is a symptom of data at different levels of detail. If you notice duplicate data, instead of creating a join, use data blending to blend on a common dimension instead.
3. You have lots of data.
Typically joins are recommended for combining data from the same database. Joins are handled by the database, which allows joins to leverage some of the database’s native capabilities. However, if you’re working with large sets of data, joins can put a strain on the database and significantly affect performance. In this case, data blending might help. Because Tableau handles combining the data after the data is aggregated, there are fewer data to combine. When there are fewer data to combine, generally, performance improves.
For more difference between data blending and joins, read this blog.
Hope this helps!