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Comparisons

By Dr Rida Akodad · Publication director · Updated 21 August 2026

Comparing tools is only worthwhile if the comparison acknowledges each one's strengths and names the precise point where one stops being adequate. These pages are written to that rule, under four methodological constraints.

The rules followed

  1. Start with what the other tool does well. A comparison that does not convinces nobody who uses it, and disqualifies itself immediately.
  2. Never invent a limitation. Only observable properties of a tool's model appear, never a supposed weakness or an unsourced reported defect.
  3. Name our own disadvantages. Vendor dependence, for instance, is real and appears in every comparison.
  4. Give a tipping-point criterion, not a verdict. The reader should leave with a question to ask about their own situation, not a conclusion to accept.

What actually decides the choice

Departmental experience shows that choosing a data tool rarely turns on a feature list. Three factors weigh more, and none appears in a conventional comparison table.

  1. The delay before you can start. An excellent tool available in six weeks loses to an adequate one available today, because the study starts now.
  2. What happens when data entry is interrupted. All data entry gets interrupted. A tool that loses the state of a half-filled record will be worked around, and the workaround becomes the real source of the data.
  3. What it takes to leave. A tool whose export omits the dictionary locks its users in without ever announcing it.

These three factors are used as criteria in each of the comparisons below, alongside the technical properties.

Comparisons