IoT Data Volume Calculator
Data storage from sensor count, sample rate, and retention.
About this calculator
This calculator sizes storage, bandwidth, and cloud transfer costs for a fleet of IoT sensors. It starts by inflating your raw payload size by a protocol overhead percentage (MQTT/CoAP headers, TLS framing — typically 10-30%), then multiplies that effective payload by samples-per-hour to get bytes generated per sensor per hour. Scaling by sensor count and 24 hours gives total raw bytes per day; dividing by your compression ratio (1 = none, 3 = typical gzip on sensor data, 5-10 for a columnar time-series database) gives the compressed daily volume that actually gets stored. Total storage for the retention window is just compressed daily volume times retention days — note that compression is applied before multiplying by retention days, so the total storage figure already reflects compressed size, not raw.
Bandwidth is computed as a sustained average (total bytes per second across all sensors, converted to kbps) rather than a peak figure, so it will understate the burst capacity you need if sensors report in synchronized batches rather than continuously. Monthly transfer for cloud egress-cost estimation uses the *raw* (uncompressed) daily figure times 30.44 days, which matters if your cloud provider bills egress before or after compression happens at the ingestion layer — check which applies to your pipeline. Messages per second is a simple aggregate rate (sensor count times sample rate) useful for sizing your MQTT broker or ingestion API separately from storage.
Inputs
Results
Daily raw data (MB)
10.55
How to Use This Calculator
- Enter the number of sensors in your deployment.
- Set samples per hour per sensor (e.g., 60 = one reading per minute).
- Enter the payload size in bytes per reading and your data retention period in days.
- Adjust compression ratio and protocol overhead percentage for your stack.
- Read Daily compressed data (MB), Total storage (GB), and Avg bandwidth (kbps) to size your infrastructure.
How the result changes with Number of sensors
| Number of sensors | Daily raw data (MB) |
|---|---|
| 50 | 5.27 |
| 75 | 7.91 |
| 150 | 15.82 |
| 250 | 26.37 |
What each input means
- Number of sensors
- Total sensors reporting data in your deployment.
- Samples per hour
- How many readings each sensor sends per hour. 60 = one per minute.
- Payload size (bytes)
- Raw bytes per sensor reading. Temperature float = 4 B, full JSON packet = 50-200 B.
- Data retention (days)
- How many days of historical data to store.
- Compression ratio
- Data compression factor. 1 = none, 3 = typical gzip on sensor data, 5-10 = columnar/time-series DB.
- Protocol overhead (%)
- MQTT/CoAP headers, TLS framing, packet headers. Typically 10-30%.
What each result means
- Daily raw data (MB)
- Total uncompressed data generated per day across all sensors.
- Daily compressed (MB)
- Daily data after compression.
- Total storage (GB)
- Storage required for the full retention period (compressed).
- Avg bandwidth (kbps)
- Sustained average network bandwidth needed.
- Monthly transfer (GB)
- Raw data egress per month for cloud billing estimates.
- Messages/second
- Average MQTT/CoAP message rate across all sensors.
How this is calculated
Worked example, using the default values
- Identify Input Parameters4 parametersNumber of sensors = 100, Samples per hour = 60, Payload size (bytes) = 64, Data retention (days) = 90 = 6 input(s) provided
- Calculate Daily raw dataDaily raw data = rawBytesPerDay / (1024 * 1024)10.55 = 10.55
- Calculate Daily compressedDaily compressed = compressedBytesPerDay / (1024 * 1024)3.52 = 3.52
- Calculate Total storageTotal storage = totalStorageBytes / (1024 * 1024 * 1024)0.31 = 0.31
Engine last updated . Checked against 2 independently-derived tests — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.
Frequently Asked Questions
Why does compression apply before retention, and does that mean total storage already accounts for it?
Yes. The calculator computes compressed daily volume first (raw daily bytes divided by your compression ratio) and then multiplies that already-compressed figure by retention days, so the Total Storage output reflects compressed size for the entire retention window, not raw uncompressed size.
Why might the reported bandwidth understate what I actually need to provision?
Bandwidth is computed as a sustained average — total bytes per second across all sensors, converted to kbps — not a peak figure. If your sensors report in synchronized batches (e.g., all fire at the top of every minute) rather than continuously spreading their traffic, your real peak bandwidth requirement will be well above this average, even though the average itself is accurate.
Why does monthly transfer use raw data instead of the compressed figure used for storage?
Monthly Transfer is calculated from the *raw*, uncompressed daily data volume times 30.44 days, specifically for estimating cloud egress costs. This matters because some cloud providers bill egress on data before compression happens at the ingestion layer, while others bill after — check which applies to your pipeline before using this number to budget cloud transfer costs.
How much does protocol overhead actually add to my payload size?
The calculator inflates your stated payload size by the protocol overhead percentage (default 20%, covering MQTT/CoAP headers and TLS framing) before any other calculation runs. For a small 4-byte temperature reading, even a modest 20% overhead is proportionally tiny in absolute bytes, but for larger JSON payloads the overhead can represent a meaningful chunk of total data volume — typical ranges are 10-30% depending on your protocol stack.
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