Pricing behavior — Relational Databases
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Pricing
Pricing for Google AlloyDB for PostgreSQL
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 managed Postgres-compatible relational core aligned to GCP
- Need governance patterns for multiple teams/apps
- Need a production baseline aligned to GCP operations as reliability and audit expectations increase
What gets expensive first
- Schema and performance discipline remain required
- Ecosystem alignment increases switching cost
- Cost predictability still requires budgets, tags/labels, and operational ownership
- Change management practices must be explicit when multiple teams share the database
Plans and variants (structural only)
Grouped by type to show structure, not to rank or recommend SKUs.
Plans
- Compute - provisioned instances - Billed by instance size/region; HA and read replicas add cost.
- Storage + I/O - separate drivers - Storage, backups, and I/O/operations can materially change total cost.
- Availability - pay for resilience - Multi-AZ/high availability configurations increase reliability and spend.
- Official pricing: https://cloud.google.com/alloydb/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.