[ttunguz]

Author here: I agree with you on benchmarks. It's hard to compare different databases well.

MotherDuck is an analytics database optimized for reading with columnar compression. Postgres is more of a transactional/general purpose database. Tuning it well for analytics would surely improve performance.

Most people won't tune a db with custom indices though because it can be hard, so purpose built solutions like this offer value in those cases.

The article isn't purely about performance but also ease of use. MD is an in process database so starting with it is very easy.

Glad we agree on the power within a laptop! It's underappreciated.

[m_ke]

*motherduck is not a database, it's a company commercializing a great open source project called duckdb.

[carterschonwald]

this is an important detail I couldn't figure out from the linked materials!

[ttunguz]

Good addition. I should have been more clear.

[danielmarkbruce]

How this is easier than using snowflake/bigquery etc?

The situation where it seems useful is if I'm using a jupyter notebook and I want to use it to pull data in but it's too much to fit into memory, and sqlite is too slow... which seems like a pretty specific situation to be in? And it's not data that is part of some business process that needs updating frequently?

Or I'm just missing the point entirely? I see another post about huge parquet datasets - but how do I get them? Is everyone at my company comfortable with me moving them onto my machine even if I can? Is the dataset so big it won't fit into memory? Can't I just connect my jupyter notebook to snowflake anyway? Then I'm only pulling down the data I want instead of all the data.

I guess maybe the real question is - exactly who is the buyer of this product, how much will they spend on it, and who is the user?