[kthejoker2]

Snowflake conceding they have a 700% markup between Standard and Premium editons which has zero impact on query performance is ... well, it's something. I'd start squeezing my sales engineers about that, definitely not sustainable...

Also proof that lakehouse and spot compute price performance economics are here to stay, that's good for customers.

Otherwise, as a vendor blog post with nothing but self-reported performance, this is worthless.

Disclaimer: I work at Databricks but I admire Snowflake's product for what it is - iron sharpens iron.

[drawturkey]

How do you get 700% markup? The difference between Standard and Enterprise is 50%. Enterprise does have features which do make workloads run faster, but this benchmark didn't need them.

[buttaphingas]

I've used Snowflake for the past few years, and it's worth pointing out that when it comes to overall cost, there's a lot you get with Snowflake for free. For example, they have HA across 3 AZs out of the box, included in the price and with no configuration required.

If I'm reading what Databricks published correctly, it seems that they've only used 1 driver node for this benchmark, in other words it's a dev setup. If they want to compare apples-to-apples then they should configure, and price, a multi-AZ HA set-up.

I'm not sure if this is still applicable to Photon, however - can anyone confirm?

[sagarm]

The _data_ should be replicated, but the compute infrastructure doesn't need to be. Many companies I suspect would be fine having to restart pipelines on driver failure (increasing tail latency, basically) if it yields a substantial cost reduction.