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> charging their customers for Ferraris I've seen this sort of analogy before and I don't think it's the right one here: if I get a Ferrari, I know _exactly_ w

> charging their customers for Ferraris I've seen this sort of analogy before and I don't think it's the right one here: if I get a Ferrari, I know _exactly_ what I'm getting. I'm getting a really fast, really beautiful car. I'm not too familiar with Snowflake, but I've suffered under Databricks on and off for about a decade now, and as far as I can tell, it's just a more expensive, closed way to do what I could do a lot faster and a lot easier if I didn't have to work around the obstacles that Databricks puts in my way that don't have any value other than being something that Databricks can charge my employer a ton of money for putting in my way.

onlyrealcuzzo 3y ago
Theoretically, your employer is paying Databricks, because they'd rather pay them than have a harder time finding employees with actual skills (and paying them accordingly). Additionally, it's somewhat of a standard now - so it's easy to hire other people in the org with skills using it.
- orochimaaru 3y ago
  But isn’t that something they would need to do anyway - find employees with actual skills? I mean sure, it’s how the snake oil is sold - “buy so and so saas product and you wouldn’t need to hire and can reduce cost”. I’m surprised that line can still sell today because in software it’s rarely true unless you can merge excellent talent with said product.
  - onlyrealcuzzo 3y ago
    If you work at a small startup - they are mostly parroting what large and mid-size companies are doing - regardless of the fact that they're likely to fail before they get to that size, and doing said thing might make their chances of failure higher. If you work at a large company - having a larger pool of candidates to hire from is definitely worthwhile. And, it is much easier to have a poor understanding of Databricks than a very good understanding of data engineering in general. Someone with a poor understanding of Databricks might be able to do 80% of what you can do with a great understanding of data engineering in general.
  - bushbaba 3y ago
    We outsource janitors, lunches, and other aspects of the business. Some things are not your core competency where having additional people investment detracts from your core mission. That and do you really think 99% of companies are able to build something better or cheaper than databricks. Likely not
hodgesrm 3y ago
The car example in the article is exactly backwards. Snowflake is the Toyota Camry. It's a mass market solution that fits a lot of basic use cases. Readers are conflating the licensing cost of Snowflake with total cost of ownership, which is quite different. The equation tilts further toward Snowflake as you load more data into it. It has a pretty efficient sharing model using virtual data warehouses. If you need the Ferrari, that's when you build with open source. If I want real-time response at fixed cost on large amounts of data I'm going to take ClickHouse with a customized stack every time. But not every problem needs that solution. (I work at a ClickHouse vendor and know its habits. But you could say the same about Druid or other databases.)

onlyrealcuzzo 3y ago

Theoretically, your employer is paying Databricks, because they'd rather pay them than have a harder time finding employees with actual skills (and paying them accordingly). Additionally, it's somewhat of a standard now - so it's easy to hire other people in the org with skills using it.

orochimaaru 3y ago
But isn’t that something they would need to do anyway - find employees with actual skills? I mean sure, it’s how the snake oil is sold - “buy so and so saas product and you wouldn’t need to hire and can reduce cost”. I’m surprised that line can still sell today because in software it’s rarely true unless you can merge excellent talent with said product.
- onlyrealcuzzo 3y ago
  If you work at a small startup - they are mostly parroting what large and mid-size companies are doing - regardless of the fact that they're likely to fail before they get to that size, and doing said thing might make their chances of failure higher. If you work at a large company - having a larger pool of candidates to hire from is definitely worthwhile. And, it is much easier to have a poor understanding of Databricks than a very good understanding of data engineering in general. Someone with a poor understanding of Databricks might be able to do 80% of what you can do with a great understanding of data engineering in general.
- bushbaba 3y ago
  We outsource janitors, lunches, and other aspects of the business. Some things are not your core competency where having additional people investment detracts from your core mission. That and do you really think 99% of companies are able to build something better or cheaper than databricks. Likely not

hodgesrm 3y ago

The car example in the article is exactly backwards. Snowflake is the Toyota Camry. It's a mass market solution that fits a lot of basic use cases. Readers are conflating the licensing cost of Snowflake with total cost of ownership, which is quite different. The equation tilts further toward Snowflake as you load more data into it. It has a pretty efficient sharing model using virtual data warehouses. If you need the Ferrari, that's when you build with open source. If I want real-time response at fixed cost on large amounts of data I'm going to take ClickHouse with a customized stack every time. But not every problem needs that solution. (I work at a ClickHouse vendor and know its habits. But you could say the same about Druid or other databases.)