A database comparison becomes more useful when it answers a specific question. “Which database is best?” leaves too much unstated. A more actionable question is: “Which candidates can support this workload, under these constraints, with a team that can operate them?”
Use the following brief to define that decision before collecting product claims or benchmark charts.
Describe the business operation
Choose a concrete operation: posting a payment, reserving stock, updating player state, or serving a customer account. Write down what a successful operation means and what a user would experience if it failed.
Avoid starting with the database feature list. First describe the outcome the application needs.
Draw the correctness boundary
List the records that must change together. Explain which reads must see the latest committed state and which can tolerate older data. Define what the application should do if a request times out but its final outcome is not yet known.
These questions create useful test cases. For an inventory reservation, for example, describe how concurrent requests should behave when only one item remains. For a payment workflow, define how your application identifies duplicate requests and reconciles uncertain outcomes.
Replace vague scale goals with a workload profile
Instead of writing “must scale,” document the load you intend to test. If a value is not known, record it as an open question rather than guessing.
| Workload dimension | What to record |
|---|---|
| Traffic | Normal and peak request rates, plus the mix of operations |
| Data | Initial size, expected growth, retention, and distribution |
| Queries | Representative requests, joins, filters, and reporting needs |
| Latency | The percentile objective for each critical operation |
| Geography | Application regions, user regions, and required data locations |
| Failure | The events you intend to simulate and the acceptable recovery outcome |
Keep the profile with any test results so another reader can understand the conditions behind them.
Separate constraints from preferences
A constraint is a condition that can disqualify a candidate. A preference is a trade-off your team may be willing to make.
- Hard constraints: required deployment regions, supported interfaces, data-location requirements, or an explicit recovery objective.
- Preferences: a familiar administration interface, fewer operational steps, or a preferred commercial model.
- Unknowns: migration effort, behavior during a particular failure, or cost at a workload level you have not measured.
Give unknowns an owner and a validation step. They should not silently become assumptions in the final recommendation.
Write the acceptance criteria
For each important requirement, describe a test and the evidence that would satisfy it. “Handles failure well” is difficult to assess. A defined failure scenario, an expected application outcome, and a recovery measurement are easier to examine.
Include normal operation, traffic changes, failure, recovery, and routine maintenance in the plan. Record the product edition, version, configuration, and infrastructure used.
Turn the brief into a shortlist
Use hard constraints to remove unsuitable candidates. Compare the remaining options against the same workload and evidence requirements. Explain any differences in test conditions before treating the results as comparable.
The final recommendation should connect back to the original brief. It should state where the choice fits, which trade-offs remain, and what would trigger a new evaluation.
Build and download your own evaluation brief, or read how to inspect a database benchmark.
This is an editorial evaluation framework, not a product test or vendor recommendation.