Measure events, bandwidth, storage, and retention across devices. Tune frequency, payload, overhead, compression, and replicas. See daily, monthly, yearly projections before infrastructure costs escalate.
| Devices | Sensors / Device | Interval | Payload | Metadata | Overhead | Compression | Replicas | Retention | Daily Ingest | Retention Storage |
|---|---|---|---|---|---|---|---|---|---|---|
| 5,000 | 6 | 15 sec | 1.5 KB | 0.25 KB | 22% | 2.5x | 3 | 180 days | 344.80 GB | 83.64 TB |
| 12,000 | 4 | 10 sec | 900 B | 180 B | 18% | 1.8x | 2 | 90 days | 523.92 GB | 52.59 TB |
These rows illustrate how device count, interval, compression, and replicas change ingest and retained storage.
1. Device streams
Device streams = Devices × Sensors per device
2. Active message rate
Messages per active second = (Device streams ÷ Sampling interval) × Uptime factor
3. Daily messages
Messages per day = Messages per active second × Active hours per day × 3600
4. Network message size
Network bytes per message = (Payload bytes + Metadata bytes) × (1 + Overhead %)
5. Stored message size
Stored bytes per message = (Network bytes per message ÷ Compression ratio) × Replicas × (1 + Safety buffer %)
6. Daily ingest volume
Daily ingest = Messages per day × Network bytes per message
7. Daily storage requirement
Daily storage = Messages per day × Stored bytes per message
8. Retention storage
Retention storage = Daily storage × Retention days
9. Growth forecast
Projected yearly storage = Base yearly storage × (1 + Annual growth %)^(Year − 1)
It estimates IoT telemetry volume, bandwidth, daily ingest, stored data after compression, replication impact, retention needs, and multi-year storage growth.
Telemetry often carries timestamps, device IDs, signatures, and routing fields. Metadata can materially increase message size, especially for small payloads.
A compression ratio of 2 means data becomes half as large before storage. Higher ratios reduce storage requirements, but ingest traffic still uses pre-compressed network size.
Each replica multiplies stored volume. Two replicas roughly double storage, while three replicas roughly triple it before safety buffers are added.
The calculator shows both. Peak active bandwidth uses active messaging time, while average daily bandwidth spreads total ingest across a full day.
Yes. It helps estimate transmission load, local storage pressure, and retention windows for edge gateways, brokers, and centralized data lakes.
Yes. Uptime reduces the effective message rate. Lower fleet or pipeline availability produces fewer messages and smaller data volumes.
Usually yes. A safety buffer helps cover burst traffic, schema changes, seasonal peaks, delayed compression gains, and infrastructure planning uncertainty.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.