S3 Cost Calculator
S3-like storage cost usually comes from storage (GB-month), requests, and egress. Some setups also add replication and cross-region transfer costs. This page groups common line items so you can build a realistic monthly estimate.
1) Storage + requests
Use average stored GB for GB-month billing, and add monthly request counts for GET/PUT pricing assumptions.
Inputs
Average stored (GB)
Approx 4.88 TB-month.
Starting storage (GB)
Monthly growth (%)
Months in period
Est 4,340 GB-month avg.
Storage price ($ / GB-month)
GET requests (per month)
Approx 1.9 req/sec.
Avg GET RPS
PUT requests (per month)
Approx 0.19 req/sec.
Avg PUT RPS
Est 5,253,120 GETs and 525,312 PUTs/month.
Request mix presets
GET price ($ / 1k)
PUT price ($ / 1k)
Scenario presets
Results
Estimated monthly total
$119.50
Storage cost
$115.00
GET request cost
$2.00
PUT request cost
$2.50
Inputs summary
| Item | Value |
|---|---|
| Average stored | 5,000 GB |
| GET requests | 5,000,000 |
| PUT requests | 500,000 |
2) Optional: egress
If you download data from storage (to the internet or another region/provider), add an egress line item here.
Inputs
Egress from storage (GB / month)
Avg throughput: 1.52 Mbps.
Avg throughput (Mbps)
Est 24,624 GB/month.
Pricing mode
Use tiered mode when pricing changes by volume.
Egress price ($ / GB)
Enter your provider's effective $/GB for the region/path/tier.
Scenario presets
Results
Estimated monthly cost
$45.00
Egress
500 GB
Price
$0.09 / GB
3) Optional: replication
Replication fees are often driven by changed data copied per month. Estimate replicated GB/month from write volume and churn, then apply your $/GB assumption.
Inputs
Replicated data (GB / month)
~82.24 GB/day, 7.61 Mbps.
Changed data (GB / day)
Events (per day)
Avg payload (KB)
Est 91.55 GB/day.
Est 2,432 GB/month.
Price ($ / GB)
Replication can be priced as cross-region transfer or as a feature fee.
Scenario presets
Results
Estimated monthly replication cost
$50.00
Replicated volume
2,500 GB
How to get your inputs
- Inputs: use billing exports, metrics, or logs to get real counts/GB where possible.
- Units: convert throughput (Mbps) or rates (RPS) into monthly units when needed.
- Scenarios: build a baseline and a high-usage scenario to avoid under-budgeting.
- Sources: Storage metrics, request logs, and cost exports are the best starting points.
Result interpretation
- Identify the dominant driver (storage vs requests vs egress vs replication).
- If requests dominate, consider caching or batching to reduce per-request costs.
- If egress dominates, check CDN or data locality options.
Common mistakes
- Using a single average and ignoring peak/incident scenarios.
- Double-counting or missing adjacent line items (transfer, logs, retries).
Advanced inputs to capture
- Break down storage by class and average GB-month.
- Separate request classes and counts.
- Include retrieval fees for IA or archive tiers.
- Model data transfer and replication separately.
Scenario planning
| Scenario | Storage GB-month | Requests | Egress | Replication |
|---|---|---|---|---|
| Baseline | Average | Expected | Expected | Expected |
| Peak | High | High | High | High |
Validate after changes
- Compare your estimate to the first real bill and adjust assumptions.
- Track the primary driver metric (requests/GB/count) over time.
Next steps
Advertisement
Example scenario
- Start with storage + requests, then add egress if you download data, and replication if you copy across regions.
- Many workloads are storage-dominated until egress or replication is added.
- Use baseline and peak scenarios to avoid underestimating churn or download spikes.
Included
- Storage + request fee estimate (GET/PUT) using your pricing assumptions.
- Optional egress estimate from GB/month and $/GB.
- Optional replication estimate from replicated GB/month and $/GB.
- Optional storage growth and RPS estimators.
- Scenario-based planning (baseline vs peak) in one worksheet.
Not included
- Retrieval and lifecycle transition fees for archive tiers (model separately).
- Provider-specific tiering and region complexity unless you use blended rates or scenarios.
- KMS, inventory, analytics, and additional per-feature charges.
How we calculate
- Step 1: estimate storage cost and request fees.
- Step 2: add egress if you transfer data out of storage.
- Step 3: add replication/copy line items if you move data across regions.
- Sum line items to get a monthly estimate.
FAQ
Do request fees matter for S3?
They can for millions of small objects or chatty workloads. For large objects with few operations, storage or egress usually dominates.
What drives replication cost?
Replicated GB/month (changed data), not the total stored dataset size. Estimate replication volume from writes and churn.
How do I estimate GB-month for storage?
Use average stored GB over the month. If you have daily values, sum them and divide by days in the month.
Should I separate storage classes?
Yes. If you use multiple classes, compute each class separately or use a blended rate.
Related tools
Related guides
Aurora pricing (what to include): compute, storage, I/O, and backups
A practical checklist for estimating Aurora costs: instance hours (or ACUs), storage growth, I/O-heavy workloads, backups/retention, and the line items that commonly surprise budgets.
Aurora Serverless v2 pricing: how to estimate ACUs and avoid surprise bills
A practical way to estimate Aurora Serverless v2 costs: ACU-hours, storage GB-month, backups/retention, and how to model peaks so your estimate survives real traffic.
AWS RDS cost optimization (high-leverage fixes)
A short playbook to reduce RDS cost: right-size instances, control storage growth, tune backups, and avoid expensive I/O patterns.
AWS RDS pricing (what to include)
A practical checklist for estimating AWS RDS costs: instances, storage, backups, I/O, and the line items that commonly surprise budgets.
Azure SQL Database pricing: a practical estimate (compute, storage, backups, transfer)
Model Azure SQL Database cost without memorizing price tables: compute baseline (vCore/DTU), storage GB-month + growth, backup retention, and network transfer. Includes a validation checklist and common sizing traps.
Bigtable cost estimation: nodes, storage growth, and transfer (practical model)
A driver-based Bigtable estimate: provisioned capacity (node-hours), stored GB-month + growth, and network transfer. Includes validation steps for hotspots, compactions, and peak throughput that force over-provisioning.
Advertisement
Disclaimer
Educational use only. Not legal, financial, or professional advice. Results are estimates based on the inputs and assumptions shown on this page. Verify pricing and limits with your providers and documentation.
Last updated: 2026-02-07