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Thanks! At 1M rows, I think a few things matter: Streaming: Can't hold it all in memory. Generate in chunks, write, release, repeat. Format choice: Parquet with row groups is fast and compresses well. SQL needs batched inserts (~1000/statement). Direct DB writes via COPY skip serialization entirely is usually fastest. FK relationships: The real bottleneck. Pre-generate parent PKs, hold in memory, reference for childr…
Why does this read like AI slop?
SQL Server support would certainly help you sell enterprise plans.
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This is useful. What if you ran a CLI locally that extracts just the statistical profile from prod cardinality, relationship ratios, etc. and uploaded that? We'd never touch your database, you just hand us the metrics and we match the shape.
I'd be willing to try that out :) a CLI would be great, even as a sandbox tool
Reminds me a bit of Snaplet before it embarked on its incredible journey to get acquired by Supabase and shut down. I like the concept but the painpoint has never been around creating realistic looking emails and such like, but creating data that is realistic in terms of the business domain and in terms of volume.
The code remains:
- https://github.com/supabase-community/seed - https://github.com/supabase-community/copycat - https://github.com/supabase-community/snapshot
This looks like a great project, wishing them all the best on the journey.
Reminds me a bit of Snaplet before it embarked on its incredible journey to get acquired by Supabase and shut down. I like the concept but the painpoint has never been around creating realistic looking emails and such like, but creating data that is realistic in terms of the business domain and in terms of volume.
Hey! Snaplet founder here. Want to clarify that it was not acquired by Supabase; I shutdown the startup and found roles for some of the team at Supabase. The code remains: - https://github.com/supabase-community/seed - https://github.com/supabase-community/copycat - https://github.com/supabase-community/snapshot This looks like a great project, wishing them all the best on the journey.
I also provide an option to select how to generate data for specific fields.
https://fakemydb.alles-tools.com
UI is a bit clunky - will revamp it :)
Earlier quoted context omitted.
Hey! Snaplet founder here. Want to clarify that it was not acquired by Supabase; I shutdown the startup and found roles for some of the team at Supabase. The code remains: - https://github.com/supabase-community/seed - https://github.com/supabase-community/copycat - https://github.com/supabase-community/snapshot This looks like a great project, wishing them all the best on the journey.
Thanks!! means a lot coming from you. Best of luck at Supabase.
Earlier quoted context omitted.
Thanks! At 1M rows, I think a few things matter: Streaming: Can't hold it all in memory. Generate in chunks, write, release, repeat. Format choice: Parquet with row groups is fast and compresses well. SQL needs batched inserts (~1000/statement). Direct DB writes via COPY skip serialization entirely is usually fastest. FK relationships: The real bottleneck. Pre-generate parent PKs, hold in memory, reference for childr…
Why does this read like AI slop?
I have something that gives you the data in CSV/SQL insert statements. I also provide an option to select how to generate data for specific fields. https://fakemydb.alles-tools.com UI is a bit clunky - will revamp it :)