RAID 10 Calculator
The formula
Why databases prefer RAID 10
Transactional workloads are dominated by small random writes, and RAID 10 handles those with a penalty of two I/O (write to both mirror legs) instead of six for RAID 6. Rebuilds are dramatically faster too, because a mirror rebuild copies one disk rather than recomputing parity across the whole array — hours instead of days on large volumes. That shorter window is where most of the reliability advantage lives: risk while degraded is proportional to how long the array sits without redundancy. The cost is capacity, since half of every pair is a duplicate.
Failure tolerance is probabilistic, not fixed
People say "RAID 10 survives one failure", which understates it. With eight disks in four mirror pairs the array survives any single failure and also survives many two-disk failures — specifically, any two that land in different pairs. Only when both members of the same pair die is data lost. The odds depend on whether failures are independent: random failures make a same-pair double loss uncommon, but correlated events (a shared power supply, a firmware bug across identical drives, a dropped tray) make it far more likely. Buying disks from different manufacturing batches is a cheap and genuinely effective mitigation.
Frequently asked questions
Is RAID a backup?
Can I build RAID 10 with an odd number of disks?
RAID 10 vs RAID 01 — are they the same?
Is RAID 10 worth the 50% capacity loss?
How many disks should I use?
Source & methodology
Patterson, Gibson & Katz (1988) RAID taxonomy; nested-level behaviour per SNIA RAID advisory notes; write-penalty and IOPS analysis from standard storage-engineering references.
RAID 10 explained: formula, worked example and honest limits
You are here because you need a specific number, and you want to see how it was produced before you rely on it. Searchers land on an RAID 10 page for three reasons — to plan, to compare options, and to check that somebody else’s arithmetic is honest. This tool serves all three, and everything after the calculator explains the model instead of hiding it.
Most confusion about RAID 10 comes from mixing up the input you control with the input you merely observe. The formula treats them identically, but your decisions should not: one deserves measurement, the other deserves a defensible estimate.
It helps to separate the mechanics from the interpretation. The mechanics are fixed: usable = ⌊N/2⌋ × disk size; write IOPS ≈ N/2 × single-disk; read IOPS up to N × single-disk. Anyone, anywhere, entering the same inputs will get the same 16.00 TB. The interpretation is where experience counts: whether 16.00 TB is good, normal or alarming depends on comparisons covered below, and that is the part most articles about RAID 10 never explain.
Nothing below is stock text pasted around a number: the worked example computes usable capacity = 16.00 TB from this tool’s own defaults, and the sensitivity section ranks the inputs that move the result — Number of disks first, at ≈25.0 % of the headline for a ten-percent error either way in that input. Read the sections in order and you will be able to reproduce every figure by hand.
Inside the RAID 10 calculation: formula and every input
One formula, published in full: usable = ⌊N/2⌋ × disk size; write IOPS ≈ N/2 × single-disk; read IOPS up to N × single-disk. Anything you can read, you can reproduce in a spreadsheet, and that reproducibility is the whole point of printing it rather than hiding it behind a button.
Number of disks (example value 8) is a quantity rather than a category — precision here is cheap and worth having. If the true figure falls between counts, run both and read the spread as your uncertainty.
Capacity per disk (TB) (example value 4) is a quantity rather than a category — precision here is cheap and worth having. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Throughput per disk (MB/s) (example value 250) is a measured number in the unit named by the label; the formula does not convert for you. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Disk MTBF (hours) (example value 1,400,000) is a quantity rather than a category — precision here is cheap and worth having. If the period is partial, decide whether you mean elapsed or planned time and keep that meaning across every field.
Rebuild time for one disk (hours) (example value 8) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. Use the value as of today, not as of the last time you looked — time fields drift silently.
A fully worked RAID 10 example
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Number of disks, Capacity per disk (TB), Throughput per disk (MB/s), Disk MTBF (hours). The endpoint of that chain is 16.00 TB of usable capacity, sitting in the “32.00 TB raw · 50.0% efficiency” band.
- Usable = ⌊N/2⌋ × disk size = 4 × 4.00 TB = 16.00 TB from 32.00 TB raw (efficiency 50.0%).
- The array is 4 mirror pairs striped together, so writes are served by 4 independent legs → write IOPS ≈ 4 × single-disk IOPS.
- Reads can come from either member of each pair → up to 8 × single-disk read IOPS.
- Approximate sequential throughput = 4 × 250 MB/s = 1,000 MB/s.
- Rebuild risk: during an 8-hour rebuild one mirror is degraded. Another disk failing has probability ≈ 0.0040%, but only a failure of the partner in that same pair loses data — roughly 1/7 of that, or 0.0006%.
Raw capacity — 32.00 TB. If your inputs change, this is usually the first companion figure to move.
Capacity efficiency — 50.0%. If your inputs change, this is usually the first companion figure to move.
Fault tolerance — Survives one failure per mirror pair — and often more, depending on which disks fail. Read next to the headline, this is the figure that shows the shape of the trade-off.
Sequential throughput (approx.) — 1,000 MB/s. This is the number experienced users quote when the headline alone would mislead.
Annual failure rate per disk — 0.63%. This is the number experienced users quote when the headline alone would mislead.
Overwrite any input above and every line of this example updates with it — the substitution is live, not a screenshot of somebody else’s numbers.
How far RAID 10 can reasonably move
Single-point answers invite false confidence, so the same engine was run across a band around the input that matters most here. Each row is a full recalculation of RAID 10, not an interpolation.
| Number of disks setting | Usable capacity |
|---|---|
| 80 % of the example value | 12.00 TB |
| 90 % of the example value | 12.00 TB |
| example inputs | 16.00 TB |
| 110 % of the example value | 16.00 TB |
| 120 % of the example value | 16.00 TB |
That spread — 12.00 TB at the low end, 16.00 TB at the high — is what a careful read of RAID 10 looks like: a band you can state out loud, with the reason for each edge. Reproduce it in the form above by editing Number of disks alone; the substitution steps will follow your figures exactly.
What actually moves your RAID 10
Nobody should have to guess which input matters. The engine was re-run once per field below — ten percent up, ten percent down, everything else frozen — and the results ranked by how far they moved the usable capacity. For RAID 10 the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Number of disks +10 % → RAID 10 = 16.00 TB · −10 % → 12.00 TB (the usable capacity shifts ≈25.0 %)
- Capacity per disk +10 % → RAID 10 = 17.60 TB · −10 % → 14.40 TB (the usable capacity shifts ≈10.0 %)
Number of disks is the dominant lever here: ten percent either way moves the result by about 25.0 %, from 12.00 TB to 16.00 TB. Measure that input from a document rather than from memory, and treat Capacity per disk as the second priority (≈10.0 % per ten percent). The remaining fields can sit at safe defaults without materially changing the answer — knowing which is which is what separates a careful calculation from an anxious one.
Reading the result: bands, zones and thresholds
The value above only becomes useful the moment you know what it is being measured against. The default case lands in the “32.00 TB raw · 50.0% efficiency” band, and bands are deliberately wide because real situations overlap. Before treating the band as fact, note its width: ten percent either way on Number of disks already spans 12.00 TB to 16.00 TB. The practical reading rules: ask what would have to change to move you one band. If the answer is “a small, plausible input difference”, the band itself is not the finding — the uncertainty is.
Where RAID 10 sits next to similar measures: this tool answers “how much is the RAID 10”, while the related calculators answer “what do I do about it”. Reading the result alone tends to over-weight a single snapshot; pairing it with the companion tools above turns the number into a decision.
Why RAID 10 results go wrong — and how to prevent it
Reporting the headline and quietly discarding Raw capacity. The companions are where the shape of the trade-off survives the rounding.
Reporting the headline and quietly discarding Raw capacity. The companions are where the shape of the trade-off survives the rounding.
This model has its own particular trap: Number of disks carries ≈25.0 % of the response per ten percent of error, so effort spent elsewhere is largely decorative.
Another is comparing across contexts: an RAID 10 computed with one set of conventions should never be lined up against a figure computed with another. Check the inputs behind both before ranking them.
RAID 10 verification checklist
- Compare the result with one independent method or published benchmark.
- Confirm the example values are plausible for your own situation before replacing them.
- Check Number of disks before anything else: it is the measured dominant input, ≈25.0 % of RAID 10 per ten percent.
- State, in one sentence, which convention each rate, unit or period in the form is using.
- Verify each input against its original source document, not memory.
- Repeat the ±10 % test on the inputs that matter and see whether the decision — not just the number — still holds.
Five steps from raw inputs to a figure you can defend
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — one document, one pass. Open the statement, label or record that holds number of disks, capacity per disk (tb), throughput per disk (mb/s), disk mtbf (hours), rebuild time for one disk (hours) and transcribe straight into the form. Transcription from a single source removes the mismatch errors that appear when figures are assembled from three different places. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
Step 2 — start from the case you can defend. Enter pessimistic-but-honest figures first; the optimistic run is a ceiling, not a plan. A conclusion that holds on conservative inputs holds everywhere. One decimal place more than your data supports is one decimal place of fiction.
Step 3 — measure what deserves measuring. The ranked levers above tell you where a careful figure pays off. Everything else can stay approximate, which is a licence to stop hunting for data you do not need. A figure with a date beside it becomes evidence; without one it stays an anecdote.
Step 4 — run the scenario trio. Expected, pessimistic, optimistic. The gap between pessimistic and expected is the number to plan against; the optimistic result is useful only as a ceiling. Compare the calculation to the rough guess you arrived with, and ask why they differ.
Step 5 — schedule the next run. In Technology & Computing the inputs drift quietly. Put a reminder a quarter out, re-enter the same fields, and read the change rather than the level. Compare the calculation to the rough guess you arrived with, and ask why they differ.
Where RAID 10 matters in practice
In Networks & Storage the figure computed here is usually the first one somebody asks to see. Having it — with the formula behind it — changes your position in the conversation from participant to reference. Half of a good calculation is knowing which input you would hate to be wrong about.
Professionals in Networks & Storage use this style of calculation as a screening filter before spending real money or effort: a quick RAID 10 check eliminates weak options in minutes, and the survivors earn the deeper, slower analysis. Write the figure down before moving on; memory flatters whichever number you saw last.
Re-running this page costs nothing and catches the slow drifts that never announce themselves. In Technology & Computing the expensive mistakes are rarely sudden; they are small changes in Number of disks that nobody recalculated for a year. Comparisons are cheap: run the identical calculation for the alternative and look at the gap.
RAID 10 — frequently asked questions
What affects RAID 10 the most?
Measured on this engine, Number of disks is the dominant lever: moving it ±10 % shifts the usable capacity across 12.00 TB to 16.00 TB — about 25.0 % of the headline, with Capacity per disk next at ≈10.0 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Which matters more: capacity per disk or number of disks?
For RAID 10, Number of disks wins the head-to-head (≈25.0 % against ≈10.0 % per ten-percent change). Knowing which input dominates is the difference between careful work and merely slow work.
What is a typical RAID 10?
With the example inputs on this page the result is 16.00 TB, labelled “32.00 TB raw · 50.0% efficiency”. “Typical” varies with situation, which is why every result here ships with its verdict band and its sensitivity list: they turn one figure into a range you can locate yourself inside.
How do I calculate RAID 10 by hand?
usable = ⌊N/2⌋ × disk size; write IOPS ≈ N/2 × single-disk; read IOPS up to N × single-disk is the entire method. Work the inputs in that order — Usable = ⌊N/2⌋ × disk size = 4 × 4.00 TB = 16.00 TB from 32.00 TB raw (efficiency 50.0%). — and you will reach 16.00 TB on the default figures, the same number this tool prints.
What happens to RAID 10 if number of disks changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the usable capacity goes across 12.00 TB to 16.00 TB, a swing of roughly 25.0 % around the 16.00 TB baseline. That ratio is the practical definition of how much this input matters.
Is the RAID 10 result of 16.00 TB good or bad?
The tool answers “what”, not “whether”: 16.00 TB carries the verdict “32.00 TB raw · 50.0% efficiency” for the default case, which is a starting interpretation rather than a verdict on your situation. Re-run with your own figures and compare the bands.
Can RAID 10 be negative or empty?
Yes, and that is informative rather than broken: a negative RAID 10 usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
How often should I check RAID 10?
Whenever an input changes by more than a few percent, and otherwise on the rhythm of your decisions — before a purchase, a review, a renewal. RAID 10 is a snapshot, not a subscription; stale snapshots are the most common silent error in Technology & Computing planning.
Is RAID a backup?
No. RAID protects against disk failure, not against deletion, ransomware, controller faults, fire, or a bad firmware flash propagating to every disk at once. The "R" is redundancy, not recovery — you still need independent, off-site copies.
Can I build RAID 10 with an odd number of disks?
No — the layout requires pairs. Some controllers reject an odd count outright; others build across the largest even subset and leave the spare as a hot spare.
Can this tool see the numbers I type?
It cannot. There is no submission step: the calculation happens in your browser and the result disappears when you close the page. Treat the fields above as a scratchpad rather than a form.
Key terms on this page
- Raw capacity
- 32.00 TB for the RAID 10 worked case; it sits next to the main result because it carries context the headline leaves out.
- Capacity efficiency
- 50.0% for the RAID 10 worked case; it sits next to the main result because it carries context the headline leaves out.
- Fault tolerance
- Survives one failure per mirror pair — and often more, depending on which disks fail in the default RAID 10 calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Usable capacity
- The primary output of this tool: 16.00 TB for the default inputs, computed exactly from usable = ⌊N/2⌋ × disk size; write IOPS ≈ N/2 × single-disk; read IOPS up to N × single-disk.
- Worked example
- Every substitution in order, from the example inputs to 16.00 TB — the audit trail for the headline figure.
- Verdict band
- A named zone on the range of plausible results; the example inputs land in “32.00 TB raw · 50.0% efficiency”, and your inputs may not.
- Sensitivity (±10 %)
- How far the RAID 10 moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Where the RAID 10 model comes from
The model is published arithmetic implemented exactly as written: usable = ⌊N/2⌋ × disk size; write IOPS ≈ N/2 × single-disk; read IOPS up to N × single-disk. Source of record: Patterson, Gibson & Katz (1988) RAID taxonomy; nested-level behaviour per SNIA RAID advisory notes; write-penalty and IOPS analysis from standard storage-engineering references. Where a professional version of this calculation differs, it differs in inputs and jurisdiction-specific coefficients, not in the algebra — which is why re-checking your inputs beats hunting for a second calculator.
This page is an estimation aid, not professional advice. The design rule is simple: two people entering identical figures must get identical answers. Nothing is smoothed, weighted or adjusted behind the scenes; where judgement enters, this page says so and names the input responsible.
Next steps after the calculation
Re-run the calculation with your own figures, stress the two most sensitive inputs by ±10 %, and only then act on the result.
This page was written for people who need one trustworthy number before their next decision, and the promise is that nothing above required trust. Bookmark the tool, re-run it whenever an input moves by more than a few percent, and keep the date with the number.