Warehouse Management
The control plane for the Snowflake credits you do still spend. Melt right-sizes warehouses, schedules suspends and resumes around your team’s actual hours, and enforces per-team budgets at admit-time — from the same proxy that already sees every statement.
The capabilities, at a glance.
Continuous right-sizing
Melt watches a rolling window of statements through the proxy — bytes scanned, runtime, spill, queue depth — and sets each warehouse’s size for the next hour against the workload mix it actually saw.
Schedule-aware suspend and resume
Auto-suspend stays on as a safety net, but Melt layers a calendar over it: pre-warm the BI warehouse at 7:55am Mon–Fri so the first dashboard isn’t cold; suspend the dbt warehouse at 6pm and leave it down through the weekend.
Per-team and per-workload budgets, enforced at admit-time
Melt classifies every statement and tags it by team / role / query-tag / warehouse.
Where this fits.
The 4–15-person data platform team
Owns Snowflake spend at $200k–$2M/yr scale.
The multi-tenant SaaS data team
Bills customers based on Snowflake usage.
The platform engineer adding FinOps to an agent rollout
Just shipped agentic SQL into production, watched QUERY_HISTORY 5×, and got a Slack message from finance.
Want warehouse management in your stack early?
We’re shipping this with a small group of design partners. Tell us about your workload and we’ll set you up.