Here's what nobody tells you: Databricks, Snowflake, and BigQuery all have billing models that are designed to fuck you, not help you predict costs.
Databricks: The Spark Tax Nightmare
Databricks uses "DBUs" (Databricks Units) which is basically their way of saying "we'll charge you based on how badly you configure Spark clusters." Standard DBUs start around $0.20, but good fucking luck keeping it that low. First month killed us - something like $8k because Dave left a fucking cluster running all weekend analyzing what should've been a $12 dataset.
Here's the bullshit part: Databricks charges per-second but clusters take 2-3 minutes just to fucking start up. So that "quick 30-second query" just cost you for 3 minutes. Plus, recent Databricks versions have this lovely issue where cluster warm-up pools sometimes don't actually warm anything - they just cost you money sitting idle.
If you don't have a Spark wizard on your team who knows about partitioning, broadcast joins, cluster autoscaling, and cost optimization strategies, you're going to pay 10x what you should.
Snowflake: The Auto-Scaling Money Pit
Snowflake sells you on "simplicity" with their credit system - credits cost $2-$4.65 depending on your region and how badly they want to screw you. The pitch is "don't worry about infrastructure, we'll handle it!" Translation: "we'll automatically scale your warehouse to X-Large the second you run a slightly complex query, and you'll only notice when you get the bill."
Our bill jumped from $1,200 to over $15k in one month because their auto-resume feature kept waking up warehouses every time someone looked at a dashboard. Recent Snowflake updates changed the default auto-suspend from 10 minutes to 1 minute, which sounds good until you realize the 60-second minimum billing means even checking SELECT COUNT(*) FROM orders costs you a full minute of compute. Death by a thousand micro-charges.
BigQuery: The Surprise Bill Generator
Google's $6.25 per TB processed sounds reasonable until you realize their definition of "processed" is fucking elastic. Run SELECT * on a 2TB table to check the schema? Congratulations, you just paid $12.50 to look at column names.
The "first TB free" is a lie - it's per month, and one poorly written window function can burn through that in minutes. My personal favorite disaster: Someone forgot a WHERE clause in a ROW_NUMBER() query and scanned our entire 136TB historical dataset. Error message didn't even show up until 40 minutes into the query. Bill came to $847 for what should've cost basically nothing. Check BigQuery's actual pricing documentation for the reality of how they calculate "processed data."
Pick Your Poison
- Databricks: Cheapest if you have Spark expertise. Most expensive if you're learning on production data. Support is useless until you're spending $50k/month.
- Snowflake: Expensive but works out of the box. Perfect for teams with more budget than time. Their auto-scaling is about as predictable as the weather.
- BigQuery: Unpredictable as hell. Budget 3x whatever their calculator tells you. The UI crashes when you try to cancel expensive queries.
Pricing calculators are bullshit, sales teams care about their commission not your budget, and enterprise pricing just means bigger surprises with longer contracts.
The only way to actually understand costs is through real user experiences on Reddit, Stack Overflow discussions about billing shock, Hacker News horror stories, and engineering blogs about cost disasters. Cloud FinOps best practices exist because these platforms are designed to be unpredictable.
Plan for 18 months of expensive learning before you figure out how not to get fucked.