Prisma filtering VS pure JS filtering
Greetings!
I have a decently sized dataset (10k+ records) with a couple of
I need to filter this dataset by three dimensions:
- Period -> a simple date range
- TimeRange -> a "clock" range
- Weekdays -> an array of weekdays (e.g. only Fridays and Mondays)
All filters apply to the same field:
I see two approaches:
1. Hybrid approach
- Apply
- Apply
- Simpler query, but more rows fetched -> extra work JS needs to do.
2. Full Prisma approach
- Walk from
- Keep only days that match the selected
- For each valid day, build a Prisma condition combining that day with the
- Result: a big
So I’m wondering: is it better to push everything into Prisma (option 2), or keep the query simple and filter
Performance-wise, what are the trade-offs at ~10k–20k or more rows with includes? I'm currently using PostgreSQL as my DB.
Update: option 3 -> use raw query with PostgreSQL built-in functions. Great but I loose Prisma type safety.
Thanks!
I have a decently sized dataset (10k+ records) with a couple of
includeI need to filter this dataset by three dimensions:
- Period -> a simple date range
{ from: Date, to: Date }- TimeRange -> a "clock" range
{ from: "HH:mm", to: "HH:mm" }- Weekdays -> an array of weekdays (e.g. only Fridays and Mondays)
All filters apply to the same field:
created_atI see two approaches:
1. Hybrid approach
- Apply
Periodgtelte- Apply
TimeRangeWeekdays- Simpler query, but more rows fetched -> extra work JS needs to do.
2. Full Prisma approach
- Walk from
Period.fromPeriod.to- Keep only days that match the selected
Weekdays- For each valid day, build a Prisma condition combining that day with the
TimeRange- Result: a big
ORSo I’m wondering: is it better to push everything into Prisma (option 2), or keep the query simple and filter
TimeRange WeekdaysPerformance-wise, what are the trade-offs at ~10k–20k or more rows with includes? I'm currently using PostgreSQL as my DB.
Update: option 3 -> use raw query with PostgreSQL built-in functions. Great but I loose Prisma type safety.
Thanks!
