Data Warehouse Cost Optimizer
Estimate monthly costs for Snowflake, BigQuery, Redshift with storage and compute optimization.
Worked Examples
Example 1: Mid-Sized Analytics
Problem:50TB Raw, Snowflake, 3:1 Compression, 100 Compute Hours
Solution:Storage: (50/3) * $23 = $383. Compute: 100 * $3 = $300.
Result:$683/month
Example 2: Big Data Archive
Problem:1PB Raw, Redshift, 3:1 Compression, Low Compute
Solution:Storage: (1000/3) * $24 = $8,000. Compute: $500.
Result:$8,500/month
Frequently Asked Questions
How does compression affect cost?
Most cloud data warehouses charge for compressed storage. A 3:1 or 4:1 compression ratio effectively cuts your storage bill by 66-75%. Highly repetitive data (like logs) compresses even better (10:1).
What is 'Hot' vs 'Cold' data?
Hot data is queried frequently (last 30 days). Cold data is rarely accessed (regulatory archives). Moving cold data to cheaper storage tiers (like External Tables or Archive) drastically reduces costs.
Does this include data transfer?
No. Egress fees (moving data out of the cloud) are separate and can be significant if you are constantly exporting large datasets.
Does clustering/partitioning help cost?
Yes, it reduces the amount of data scanned (partition pruning), which directly lowers compute costs (less I/O, less CPU time).