I'm learning Django and its ORM data access methodology and there is something that I'm curious about. In one particular endpoint, I'm making a number of database calls (to Postgres) - below is an example of one:
projects = Project.objects\
.filter(Q(first_appointment_scheduled=True) | (Q(active=True) & Q(phase=ProjectPhase.meet.value)))\
.select_related('customer__first_name', 'customer__last_name',
'lead_designer__user__first_name', 'lead_designer__user__last_name')\
.values('id')\
.annotate(project=F('name'),
buyer=Concat(F('customer__first_name'), Value(' '), F('customer__last_name')),
designer=Concat(F('lead_designer__user__first_name'), Value(' '), F('lead_designer__user__last_name')),
created=F('created_at'),
meeting=F('first_appointment_date'))\
.order_by('id')[:QUERY_SIZE]
As you can see, that's not a small query - I'm pulling in a lot of specific, related data and doing some string manipulation. I'm relatively concerned with performance so I'm doing the best I can to make things more efficient by using select_related() and values() to only get exactly what I need.
The question I have is, conceptually and in broad terms, at what point does it become faster to just write my queries using parameterized SQL instead of using the ORM (since the ORM has to first "translate" the above "mess")? At what approximate level of query complexity should I switch over to raw SQL?
Any insight would be helpful. Thanks!