feqgmmr2

I think it's important to understand how this kind of scenario comes up. It's unusual to want to move a whole PB at one time, and yeah in that case these other costs would come up. Problem is, the cost is more insidious than that.

Consider a scenario where data is coming in periodically, say daily, from some source, server logs, sensor data, whatever. And the user wants to train models daily on the data and they also want to do some SQL. Maybe they ingest the data directly into SF and copy it out for training, or they do it the other way round, land it in object store and the ingest into SF. This is unlikely to be a humongous amount of data, it's probably not a PB. However, this adds up, maybe for some use cases it becomes a PB in a month, maybe in a quarter, maybe it only adds up to a PB in a year.

Thing is, without a Lakehouse architecture, the user will pay to store and copy that data multiple times (at least twice) no. matter. what. They may not pay for a PB in one shot, but you can bet that eventually they'll pay multiple times to store and copy that PB.

It's very relevant if you ever want to do serious ML or anything other than SQL. Of course Snowflake wants you to think that you never need another platform. Every customer knows that's not the case.

This is exactly what FAANGs do with their data platforms. There are literally hundreds of groups within these companies with very strict data isolation requirements between them. Pretty sure something like that is either already possible or will be very soon, there's just too much prior art here.

It is not a "small" cost. The cost is proportional to the size of the data exported.

For all intents and purposes, large amounts of data are locked into Snowflake. Is it theoretically possible to export a petabyte out of SF? Sure.

Do I want to spend money on it? Not really. That is what I mean by the "data doesn't come out".

"Exporting" a petabyte out of Databricks is a no-op. I can already read Deltalake from other open source tools.

Do you have to pay to export data out of Snowflake? Yes. They have a nice guide on how to spend money doing it (https://docs.snowflake.com/en/user-guide/data-unload-overvie...).

Do you have to pay to export data out of Databricks? No, it's already sitting where you want it.

Which one is open? I wonder

Spark has always been able to handle way larger scale than any DW.

The 'open' here refers to the data. Delta lake can be read/written by multiple open source engines, not just Spark. Not to mention, if you want you can use Databricks with Parquet, though the experience won't be as good.

But with Snowflake, the data never comes out. Can't use Spark/Trino/Flink... on data in SF.

If you want Python, ML and SQL to be easily usable together on the same data nothing can touch Databricks.

The thing is even that response doesn't show them to be better. As someone pointed out, they're comparing their cheapest offering with Databricks' most expensive one and saying they're 3% better in price-perf. What does someone read into that?