I am pretty familiar with the Django ORM where you hit limitations fairly early (if you are writing any moderately complex queries). But I still use it for maybe 90% of the stuff I do because that 90% involves pretty simple queries, and it saves a ton of typing, and integrates well with the rest of the Django ecosystem.
Updating data is a good example. I recently split up some database strings into multiple columns. At first I just wrote the SQL to update a joined table. Then I needed to get regexes involved to pull out certain parts of the string. Doing that in SQL gets ugly, and its far simpler just to use the ORM to pull out the data required and operate on it in Python on a loop.
I don't see the ORM as an either / or, but as a complimentary tool to SQL.
I am pretty familiar with the Django ORM where you hit limitations fairly early (if you are writing any moderately complex queries). But I still use it for maybe 90% of the stuff I do because that 90% involves pretty simple queries, and it saves a ton of typing, and integrates well with the rest of the Django ecosystem.
Updating data is a good example. I recently split up some database strings into multiple columns. At first I just wrote the SQL to update a joined table. Then I needed to get regexes involved to pull out certain parts of the string. Doing that in SQL gets ugly, and its far simpler just to use the ORM to pull out the data required and operate on it in Python on a loop.
I don't see the ORM as an either / or, but as a complimentary tool to SQL.