Object Storage Cost Calculator (GB-month + requests)
Object storage costs usually come from stored data and request volume. Use this calculator to estimate the blended monthly cost and compare baseline vs peak traffic.
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 |
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.
Result interpretation
- Storage GB-month is steady; requests spike during traffic bursts or batch jobs.
- If requests dominate, review object size and access patterns.
Common mistakes
- Using a single average and ignoring peak/incident scenarios.
- Double-counting or missing adjacent line items (transfer, logs, retries).
Scenario planning
| Scenario | Stored GB | GET/PUT | Notes |
|---|---|---|---|
| Baseline | Average | Expected | Normal traffic |
| Peak | Same | High | Batch/launch |
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
- 5,000 GB stored, plus 5M GET and 500k PUT requests at your request pricing -> estimate monthly cost.
- 20 TB stored with low request volume -> storage dominates; requests are usually a rounding error.
- Peak 220% scenario shows how request surges impact total cost.
Included
- Storage cost estimate from average GB stored and $/GB-month pricing.
- Request cost estimate for GET and PUT from request counts and per-1k pricing.
- Optional storage growth, RPS, and request mix presets.
- Baseline vs peak scenario table for request spikes.
Not included
- Retrieval fees, lifecycle transitions, replication, and tiered pricing (model separately).
- Bandwidth/egress charges (use Data Egress Cost Calculator).
How we calculate
- Storage cost = average stored GB x storage price per GB-month.
- Request cost = (requests / 1,000) x price per 1,000 for each request type.
- This simplified model excludes retrieval fees, lifecycle transitions, replication, and tiered pricing.
FAQ
Why use average stored GB?
Billing is typically per GB-month. If your storage grows over the month, use the average (midpoint) rather than the end-of-month number.
Do egress costs belong here?
Not in this tool. Use the Data Egress Cost Calculator for bandwidth-based costs.
What about different storage classes?
Different classes (standard, infrequent access, archive) can have different storage, request, and retrieval pricing. Model each class separately if needed.
How do I estimate replication or cross-region copy costs?
Replication/copy can add per-GB and/or transfer fees, plus extra replica storage. Use the Storage Replication calculator for the replication fee and add replica storage here as another line item.
Do small objects increase cost?
Many small objects often increase request volume (PUT/LIST/GET), which can increase request fees. If you store millions of small objects, request costs can become material.
Related tools
Related guides
Estimate RDS backup storage (GB-month) from retention and churn
A practical method to estimate RDS backup storage (GB-month): start from daily changed data, retention days, and sanity-check with snapshot sizes. Includes common mistakes that inflate backup cost.
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.
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.
Cloud Spanner cost estimation: capacity, storage, backups, and multi-region traffic
Estimate Spanner cost using measurable drivers: provisioned capacity (baseline + peak), stored GB-month (data + indexes), backups/retention, and multi-region/network patterns. Includes a worked template, common pitfalls, and validation steps.
Cloud SQL pricing: instance-hours, storage, backups, and network (practical estimate)
A driver-based Cloud SQL estimate: instance-hours (HA + replicas), storage GB-month, backups/retention, and data transfer. Includes a worked template, common pitfalls, and validation steps for peak sizing and growth.
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: 2026-02-23