Before using a benchmark to support a database decision, ask what was tested and whether those conditions match your workload. A performance chart is easier to interpret when the configuration, measurement method, and limitations sit beside it.
This checklist helps you inspect the evidence. It does not substitute for testing your own application.
Start with the question behind the chart
Identify the operation being measured. Is the test about point reads, updates, analytical queries, a transaction mix, or a full application flow? Write down the data model and the business behavior the operation is intended to represent.
Then ask what the test excludes. A narrow test can be useful, provided its conclusion remains narrow too.
Inspect the comparison conditions
Check whether each candidate’s environment is described well enough to understand the comparison. Record differences rather than assuming identical conditions.
| Area | Questions to ask |
|---|---|
| Product | Which version, edition, and deployment model were used? |
| Infrastructure | What compute, memory, storage, network, and regions were involved? |
| Data | What was the dataset size, distribution, and working set? |
| Configuration | Which consistency, durability, replication, and tuning choices were made? |
| Client | Where did the load generator run, and could it constrain the test? |
| Timing | How were warm-up, test duration, repeated runs, and failures handled? |
If a material setting is missing, identify it as a limitation on your interpretation.
Read throughput and latency together
Ask how the test changed offered load and what happened to response time, errors, and timeouts along the way. Look for percentile measurements relevant to your application, not just a single average.
Check which requests were counted as successful. If errors or retries are excluded from the headline result, understand their volume and effect before using the number in an estimate.
Ask about correctness and recovery
A normal-operation performance test does not establish behavior during a node failure, network disruption, or recovery. Look for separate evidence for those scenarios.
Define what your application needs to preserve when a failure occurs. Ask how the test checked the resulting data, resolved uncertain requests, and measured the return to acceptable service.
Look for reproducible materials
A result is easier to examine when the article provides the test scripts, configuration, data-generation approach, raw outputs, and aggregation method. Note any dependencies that prevent you from repeating the procedure.
Distinguish a vendor-provided result from an independently executed test. Neither label removes the need to inspect the setup, and neither should be inferred from the appearance of the website presenting it.
Bring the result back to your decision
Write a short interpretation with three parts:
- Observed: what the reported test actually measured.
- Relevant: which requirements in your workload it helps evaluate.
- Still unknown: what you need to test before making a decision.
This keeps a benchmark useful without asking it to answer questions outside its scope. Use the evaluation brief to connect the evidence to your own requirements, and read our methodology for the standard we intend to apply to future comparisons.
This article is a reading checklist. Database Lens has not run or published a benchmark as part of this guide.