Example data table
Use these sample values to verify the calculator output and exports.
| Scenario | Model | Stored | Util. | Redundancy | Growth | Horizon | Typical outcome |
|---|---|---|---|---|---|---|---|
| Lab NAS refresh | On‑prem | 50 TB | 80% | 1.33× | 15% | 3 years | CapEx dominates in year 1; OpEx steady. |
| Cold archive | Cloud | 120 TB | 90% | 1.10× | 8% | 5 years | OpEx dominates; egress can change totals. |
| Compliance split | Hybrid | 80 TB | 75% | 2.00× | 20% | 4 years | Mix of yearly CapEx and recurring cloud fees. |
Formula used
- Raw capacity required (TB): Raw = (Stored ÷ Utilization) × RedundancyFactor
- Growth: Storedy = Stored0 × (1 + g)^(y−1) (compounded annually)
- Incremental CapEx (on‑prem): purchase only added raw TB each year
- Power cost (year): kWh = (Watts × 24 × 365) ÷ 1000; Cost = kWh × Price × CoolingFactor
- Space cost (year): U = AvgTB ÷ (TB per U); Cost = U × MonthlyCost × 12
- Cloud storage fees (year): AvgGB × PricePerGBMonth × 12 + FixedFees × 12 + EgressGB × EgressPrice × 12
- NPV (year y): NPVy = Costy ÷ (1 + d)^y
How to use this calculator
- Choose a deployment model: on‑prem, cloud, or hybrid.
- Enter the stored capacity you must keep available.
- Set utilization and redundancy to match your reliability target.
- Provide growth, horizon, and an optional discount rate.
- Fill cost drivers for the selected model(s) and submit.
- Review yearly breakdown, then export CSV or PDF for records.
Capacity drivers and planning horizon
Storage spend is dominated by the usable capacity you must guarantee over time. Start with retained data, then apply utilization and redundancy to convert it into raw provisioned capacity. A 70% utilization target builds headroom for peaks, rebuilds, and maintenance windows. Redundancy (parity, replicas, or multi‑zone copies) multiplies capacity again and often becomes the biggest lever. Include snapshots, backup retention, and index/metadata overhead so the baseline reflects reality.
On‑prem cost structure
On‑prem estimates should combine capital and operating components. Hardware price per terabyte is only the entry point; controllers, enclosures, racks, networking, and spares add overhead. Annual maintenance, power, cooling, and floor space convert CapEx into a steady run‑rate. You can annualize CapEx across useful life to compare with subscription pricing. Add staffing time for monitoring, patching, and incident response when storage is business‑critical.
Cloud pricing components
Cloud storage is billed per GB‑month, but the effective rate depends on tier, requests, and movement. Minimum storage durations, retrieval fees, and fixed platform charges can shift the average. Data egress is frequently underestimated; even modest outbound traffic can rival storage fees for analytics or media workloads. Model multiple scenarios by varying egress and access frequency. If lifecycle rules move older data to colder tiers, treat pricing as a blended average across tiers. Include request charges where workloads are highly transactional, and validate unit prices against your region and contract terms carefully.
Hybrid optimization approach
Hybrid designs mix predictable on‑prem base capacity with elastic cloud burst or archive. A practical method is to keep hot, latency‑sensitive datasets local, while pushing cold data to lower‑cost object tiers. Compare hybrid totals to pure models using the same growth rate and horizon. Iterate the split percentage until savings flatten against added operational complexity. Also test whether cloud replicas replace some local redundancy, reducing raw multipliers without sacrificing resilience.
Using discounting and sensitivity
For multi‑year comparisons, discounting translates future payments into today’s value. Applying a discount rate produces an NPV view that highlights long‑term commitments and timing effects. Run sensitivity checks by varying growth, utilization, and redundancy because small changes can amplify year‑over‑year spend. Report results as annual totals and as cost per TB‑month to benchmark vendors. Keep the estimate alongside real invoices so assumptions are continuously calibrated and improved.
FAQs
1) What does “utilization target” mean?
It is the maximum fill level you plan to operate at. Lower targets reserve headroom for peaks, rebuilds, and performance, but increase required raw capacity and cost.
2) How should I choose a redundancy factor?
Use a factor that reflects your protection method: parity overhead, mirroring, replicas, or multi‑zone copies. If you are unsure, start with 1.3–2.0 and refine after architecture review.
3) Why include data egress in storage cost?
Outbound transfer can be billed separately and may exceed storage charges for analytics, backups, or customer downloads. Estimating egress prevents surprises when usage grows.
4) What is the difference between TCO and NPV here?
TCO is the summed nominal spend over the horizon. NPV discounts future years to today’s value using your discount rate, helping compare timing and long‑term commitments.
5) How can I reduce storage costs without risking reliability?
Apply lifecycle policies, compression, deduplication, and retention limits. Improve utilization with monitoring and cleanup, and match redundancy to the true recovery objective rather than over‑provisioning.
6) Does this calculator replace vendor quotes?
No. It is a planning model that standardizes assumptions across options. Use it to shortlist architectures, then validate unit prices and constraints with vendor quotes and real usage data.