Pricing behavior — Relational Databases
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Pricing
Pricing for Neon
How pricing changes as you scale: upgrade triggers, cost cliffs, and plan structure (not a live price list).
Sources linked — see verification below.
Freshness & verification
Pricing behavior (not a price list)
These points describe when users typically pay more and what usage patterns trigger upgrades.
Actions that trigger upgrades
- Developer workflow becomes a bottleneck for shipping
- Need fast environment creation for previews and CI
- Need branching/ephemeral database workflow to reduce friction in development and testing
What gets expensive first
- Production requirements must be validated early (limits, performance, observability expectations)
- Operational model differs from traditional managed Postgres
- Cost predictability can change quickly as branches and environments multiply
Plans and variants (structural only)
Grouped by type to show structure, not to rank or recommend SKUs.
Plans
- Usage-based - compute + storage - Costs rise with active compute time, storage growth, and branching usage.
- Limits - concurrency matters - Connection limits and compute sizing drive which tier fits production.
- Workflow - branching/ephemeral envs - Great for dev speed, but validate production limits early.
- Official pricing: https://neon.tech/pricing
Next step: constraints + what breaks first
Pricing tells you the cost cliffs; constraints tell you what forces a redesign.
Open the full decision brief →Sources & verification
Pricing and behavioral information comes from public documentation and structured research. When information is incomplete or volatile, we prefer to say so rather than guess.