A pattern I see constantly. A team adopts an API testing tool because a colleague liked it or it topped a listicle, and then quietly reshapes their testing to fit whatever the tool happens to be good at. It is backwards. The tool should serve the kind of testing you need, not define it.
API testing is not one activity
The phrase API testing gets used as if it names a single task, but it covers several very different jobs. Functional testing checks that an endpoint returns the right response for a given input. Integration testing checks that services actually talk to each other correctly. Load and performance testing check what happens under stress. Security testing probes for the ways an endpoint can be abused. Contract testing checks that a change on one side does not silently break the other.
These are not variations on one theme. The different types of api testing answer genuinely different questions, and a suite that is strong on one can be completely blind to another.
Tools are good at different subsets
Once you accept that, the tooling conversation changes. No single tool is equally good at all of these. Some are excellent at functional and regression checks and weak at load. Some are built for performance and awkward for contract testing. Some shine at capturing real traffic and turning it into cases, and others expect you to hand author everything.
This is why comparing api testing tools in the abstract is close to meaningless. A tool is only good or bad relative to the kind of testing you are actually trying to do. The right question is never which tool is best. It is which tool is best for the type of testing your risk profile demands.
Start from the risk, not the feature list
So before you look at a single tool, I would work out where your actual exposure is. A payments API lives and dies on correctness and security, so functional and security testing dominate. A high traffic public API might rise or fall on performance, so load testing matters more. A system of many small services stitched together is one contract change away from an outage, so contract and integration testing earn the attention. The dominant risk tells you which type of testing to invest in first, and only then does the tool question make sense.
What good coverage looks like across types
The strongest suites I have worked with are deliberately uneven. They go deep on the one or two types that match their biggest risks and keep the others at a sensible baseline. That is a feature, not a gap. Trying to be equally thorough across every type is how teams end up spread thin, with a lot of shallow checks and no real depth anywhere.
It also helps to be honest about what each type cannot do. Functional tests will not catch a performance cliff. Load tests will not tell you a response body is subtly wrong. Security scans will not verify business logic. Knowing the blind spots of each type is how you decide what actually needs a second type layered on top.
Where the tool finally comes in
Only after the types are settled does tool selection get easy, because now you have real criteria. You know whether you need traffic capture or hand authored cases, whether performance is a first class concern or an afterthought, whether contract testing has to be part of the pipeline. The lists that felt overwhelming become simple to filter, because most of the options do not do the thing you actually need, and the ones that do are obvious.
Where this leaves me
The teams that get the most out of API testing almost never start with the tool. They start by naming the kinds of failure they cannot afford, map those to the types of testing that catch them, and only then choose tools that are strong where it counts. Do it in that order and the tool feels like it fits. Do it in reverse and you spend a year bending your testing around a tool that was never designed for your problem.