When budgets tighten, the first thing that gets cut is the ability to use your own data. Here’s how to cut costs without cutting capability.
Calculate Your SavingsIt’s not storage. The real expense is the human and infrastructure tax on querying — the cost of keeping your data usable, not just stored.
Reduce spend without reducing what your team can do.
Capacity pricing means queries cost $0 incremental. Your AI agents, dashboards, and analysts don’t compete for budget.
From $53/day + $40/day per TB
Replace 5–7 data infrastructure contracts with one. When procurement freezes hit, you’re not renegotiating with five vendors. You’re not managing five relationships.
A web engineer or full-stack dev can build what used to require a dedicated data engineering team. Not fewer people — more output per person.
In a downturn, companies that can still run AI against their data have an edge. Per-query pricing makes that unaffordable at scale. We make it free.
| Traditional Stack (Annual) | Cost |
|---|---|
| Snowflake / Databricks | $100K–$600K (scales with queries) |
| ETL tooling | $50K |
| Search cluster | $40K |
| FinOps / monitoring | $30K |
| 2 additional specialist hires | $360K |
| Total | $1M+ |
| MinusOneDB (Annual) | Cost |
|---|---|
| Pro instance + 1TB storage | ($96 + $80) × 30 × 12 = $63K |
| Additional hires needed | 0 |
| Per-query overage | $0 |
| Total | $63K |
Looking to cut 20–30% from data infrastructure without losing capability. One vendor, predictable billing, no query surprises.
Consolidating vendors during a procurement freeze. Replace a sprawling stack with one platform that does more with less.
Whose team spends more time on infrastructure than product. Get your engineers back to building what matters.
Deploying AI agents that are hitting per-query cost walls. Capacity pricing means your agents run without a meter.