Compare Data Warehouse Costs
Enter one workload to estimate Snowflake, BigQuery and Redshift side by side, using current public pricing and explicit sizing assumptions.
Your workload
Estimated billed query bytes drive BigQuery only. Independently estimated runtime and capacity drive Snowflake and Redshift. These inputs do not imply equal performance or latency. Query data is billable volume after query-level minimums and rounding; a monthly total cannot infer caching or pruning.
Sizing assumptions and allowances
Snowflake: one Standard Gen1 X-Small warehouse in AWS Northern Virginia. Redshift: editable average billed RPUs in AWS US East, independent of Snowflake size. BigQuery: Iowa on-demand queries and active logical storage. Regions differ. Blank billed-storage overrides use the logical storage quantity; no compression or additional retained-data adjustment is assumed. Remaining BigQuery allowances start at zero.
Cost comparison
Enter your workload and choose Compare costs to see estimates.
This is a scenario model, not a benchmark. Snowflake credits, BigQuery billable bytes and Redshift RPU-hours measure different things. Storage measurements and regional scope also differ. Individual calculator inputs are not carried across links.
How to read the results
- Snowflake: useful when you can estimate warehouse runtime and want to budget credits; starts and resizes can change the bill.
- BigQuery: useful when billed bytes are predictable; caching, pruning and per-query billing rules affect actual usage.
- Redshift: consider alongside an existing AWS architecture; choose RPUs from an independently sized workload, not from Snowflake credits.