Pricing behavior — Relational Databases
•
Pricing
Pricing for Amazon Aurora (Postgres)
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 deeper AWS integration and managed database operations
- Need to standardize database governance for multiple teams
- Need a production baseline with clearer operational controls as reliability requirements increase
What gets expensive first
- Database migrations and governance remain your responsibility
- Performance tuning and cost management require disciplined ownership
- Ecosystem alignment increases switching cost; plan for exit/migration strategy early
- Cost visibility requires tagging/budgets and operational discipline
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://aws.amazon.com/rds/aurora/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.