AWS RDS pricing (what to include)
RDS pricing varies by engine and storage type, but a simple cost model usually gets you close enough for planning: compute + storage + backups + (optional) I/O.
RDS cost components (checklist)
- Compute: instance-hours for primary + read replicas + any standby capacity (Multi-AZ).
- DB storage: GB-month (and sometimes provisioned IOPS/throughput depending on storage type).
- Backup storage: GB-month for automated backups + manual snapshots + copied snapshots.
- I/O: only for pricing models that charge per request; otherwise treat as performance risk, not a billing line.
- Extras: monitoring/log exports, data transfer between AZs/regions, and encryption-related operations (varies by setup).
1) Start with compute (instance hours)
For budgeting, model instances x hours/month x $/hour. If you have read replicas or Multi-AZ, model them as extra instances.
- If you scale by environment (prod vs staging), budget each environment separately. Non-prod often wins most from schedules and right-sizing.
- If you plan to commit (Reserved Instances / Savings Plans), use an effective $/hour and validate break-even utilization. Related: Reserved vs on-demand.
2) Add database storage (GB-month)
Storage is typically billed per GB-month. Use your expected allocated storage (or average used storage if your plan bills that way).
- Storage type matters. Some options add line items for provisioned IOPS and throughput.
- Model growth over 3–12 months. Storage growth frequently beats compute as the long-term driver. Tool: DB storage growth.
3) Model backups and snapshots
Backup storage can be a steady monthly cost, especially if you keep long retention or frequent snapshots. Use a separate estimate for backup GB-month.
Next: Backups & snapshots (how to estimate).
- Split backups into operational retention (days/weeks) vs long-term snapshots (months/years).
- Confirm whether you copy snapshots cross-region or cross-account (often overlooked in budgets).
- If you already have an RDS footprint, validate from Cost Explorer before trusting a forward estimate: backup storage is visible as a usage-based line item.
4) Include I/O only if your pricing model charges for it
Some storage models charge per I/O request. If you don't have a reliable I/O estimate, run two scenarios: \"low I/O\" and \"high I/O\".
Even when I/O is “free” in pricing, I/O patterns still matter because they drive instance sizing and performance risk.
5) Use a calculator for fast scenario planning
Use AWS RDS Cost Calculator to model instance hours + storage + backups + I/O with your own pricing assumptions.
Worked example (build a defensible budget)
- Choose instance class and count (primary + replicas/standbys).
- Choose storage GB and expected monthly growth.
- Estimate backup storage using churn × retention (add long-term snapshots separately).
- Add a peak scenario (batch jobs, incidents) to understand downside risk.
If you can’t justify the inputs in one sentence each (“where this number comes from”), the estimate will not survive budget review.
How to validate after you deploy (so the model stays true)
- In Cost Explorer, filter Service to Amazon RDS and group by Usage type to see the top drivers (instance-hours, storage, backup storage, I/O if applicable).
- Cross-check storage and growth from RDS metrics and your DB telemetry. If growth differs, fix the model (not the spreadsheet).
- If backup storage is higher than expected, audit retention settings and manual snapshots. Related: snapshot retention cost model.