Pricing behavior — Relational Databases
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Pricing
Pricing for PlanetScale
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
- Need MySQL relational core with modern developer workflows
- Need scaling patterns that outgrow simple managed MySQL assumptions
- Need a platform workflow that keeps developer iteration fast as schema and environments grow
What gets expensive first
- Validate production constraints and cost drivers early
- Switching costs exist if data model and workflow become coupled
- Have an explicit exit plan if requirements later force a different operating model
- Compatibility choice (MySQL vs Postgres) tends to be the biggest long-term constraint
Plans and variants (structural only)
Grouped by type to show structure, not to rank or recommend SKUs.
Plans
- Compute + storage - primary drivers - Pricing usually scales with compute size, storage, and traffic patterns.
- High availability - replicas/backups - Reliability features add cost but reduce operational risk.
- Governance - migrations/ops - Performance tuning and migration ownership remain your responsibility.
- Official pricing: https://planetscale.com/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.