At least they have useful technical information in it. Personally really like reading these blog posts.

Measurements and context is so situational that it would be useless anyway imo.

It is not like any DB company is writing blog posts with benchmarks compared to hardware limits. DuckDB had blog posts that has sentences like "You are doing it wrong if you are not using HTTP api on your database in 2026", last time I saw their blog.

I also think object storage is bad in this case. And rust is no a no-no for a database project like this, because it is not ergonomic to do static allocation and arena allocators in rust. And parquet is trash for performance because of many reasons like supported compression formats etc.

You're not wrong: if you know how much memory you need for a single query and can keep the data in attached SSD (so ephemeral SSD on AWS), scaling vertically will give you the fastest execution time.

However horizontal scaling has advantages in that it's easier to scale up and down incrementally. It gives you more aggregate network bandwidth for accessing disaggregated data. Disaggregation allows for independent scaling of compute and storage. Losing a single machine has a marginal impact on the cluster, which can enable you to use cheaper spot resources.

Basically, it's often easier to operate a system designed around horizontal scaling if you need resiliency.

group by is useful with other aggregates like sum, max, and so on.