Comparisons
Pairs that get conflated in real conversations and in real pull requests — coupling and cohesion, abstraction and indirection, refactoring and rewriting, debt and mess. Neither column wins; what decides is the requirement. Each record leads with the confusion, because the confusion is the reason the record exists.
Library vs Framework
The inversion-of-control definition is correct and people repeat it without drawing the consequence, which is about *change*, not about who calls whom. Because a framework owns the lifecycle, its assumptions become constraints on your design: where your logic can live, what your types may look like, how your code is initialised and torn down, what your tests must boot. That is often a good trade — a team of eight shipping a standard web application should almost never build their own conventions — but it means the framework's upgrade schedule and its eventual decline become your problems, and it means your business rules will drift toward its shapes unless you deliberately keep them out. The second confusion is the belief that you must choose one posture for the whole system. You do not: the productive arrangement is a framework at the edge, where its conventions do the boring work, and a core of ordinary functions and types that does not import it at all. That is the entire practical content of "keep the domain framework-free", and it is also how you find out, five years later, that migrating frameworks is a week rather than a year.
When you want a capability without surrendering control of your program's shape: a date parser, an HTTP client, a validation kernel. Libraries compose, and two libraries rarely fight.
When the conventions are the value — routing, lifecycle, dependency wiring, build integration, a well-trodden path for a team that should not be inventing one. A framework is a bet that its assumptions match your problem for years.
| Dimension | Library — you call it | Framework — it calls you |
|---|---|---|
| Control flow | Yours; you call in | Theirs; you fill in extension points |
| Constrains your structure | Barely | Substantially, and increasingly over time |
| Composability | High — several libraries coexist easily | Low — two frameworks in one process is a fight |
| Replacement cost | Local: change the call sites | Global: the shape of the app was theirs |
| What you get for it | A capability | Conventions, wiring, ecosystem and a path everyone knows |
| Testing | Ordinary functions; nothing to boot | Often needs the container or runtime to be started |
| Upgrade risk | Contained to the API you use | Can force changes across the whole codebase |
| Best arrangement | Anywhere, including inside the domain | At the edge, with the domain not importing it |
The same question, five structures
Layered, hexagonal, clean, vertical slice and modular monolith — compared without naming a winner, and with the block that says where the comparison stops being true.
A tidy table implies an equivalence that does not exist. These are not five points on one axis: layered, hexagonal and clean are statements about dependency direction; vertical slice is a statement about directory grouping; modular monolith is a statement about deployment and module visibility. Most real systems combine several. The where this comparison misleads block on every row is the part worth reading, and it is the reason this page names no winner — none of these is mandatory, and a team that adopts one because a diagram was pretty has skipped the only question that decides it.
These are not five points on one axis. Layered, hexagonal and clean are all statements about *dependency direction*; vertical slice is a statement about *directory grouping*; and modular monolith is a statement about *deployment and module visibility*. You can — and most real systems do — combine several of them: a modular monolith whose modules are vertical slices, each with a hexagonal boundary at its edges. Comparing them as alternatives is the single most common way this table is misread.
The word complexity is doing two jobs here. Layered and vertical slice are cheap to *set up* and can be expensive to *live in* once the codebase is large; clean and hexagonal are expensive up front and their cost is roughly flat afterwards. Any comparison made at week one inverts the ranking you would get at year three, and neither reading is dishonest — they are answering different questions.
Locality is a property of whether the boundaries match the change history, not of the style name. A vertical slice cut along the wrong capability lines has terrible locality, and a layered codebase with only one real feature has perfect locality. The only honest way to compare these columns is to open the last thirty merged changes in your own repository and count the directories each one touched.
Every column here is a claim about *fast tests without infrastructure*, and any of the five achieves that as soon as dependencies are injected rather than constructed — which is a separate decision none of these styles owns. What differs is the default test boundary each one nudges you toward, and that matters more than the theoretical maximum: layered nudges toward class-level tests with mocks, vertical slice toward feature-level tests, and the difference shows up in how much your suite has to change during a refactor.
The columns are answering to different pressures: hexagonal responds to *external* volatility, clean to *domain* richness, vertical slice to *feature count*, and modular monolith to *team count*. A system can score high on one pressure and low on the rest, which is why picking a style from a comparison table rather than from your own pressures is how teams end up with four rings around a CRUD application.
Team fit is not a tiebreaker, it is often the deciding factor, and it is the one this table cannot capture. A structurally superior design that the team will not maintain under deadline degrades into the worst version of itself — half-applied clean architecture, with some code respecting the ring rule and some not, is harder to work in than consistent layering. The right question is which of these your team will still be following in eighteen months.
This row compares familiarity, not intrinsic difficulty, and familiarity is a property of the industry at a moment in time rather than of the design. Layered wins here largely because it is what most people have seen, which is an argument for it and also the reason it is over-applied. It is also worth separating cost-to-read from cost-to-contribute-correctly: vertical slice inverts on those two, and the table's single number hides it.
Ceremony is only waste when the feature did not need it, and every column here is right for some features and wrong for others in the same codebase. That is the actual finding of this row: a uniform ceremony level applied to every feature guarantees you are overpaying on the simple ones or underpaying on the complex ones. Allowing different features to carry different amounts of structure is more valuable than choosing which column to standardise on.
shared/ directory that grows back under a new name, or slices that each reimplement infrastructure slightly differently.Every one of these degradations is the style's own strength taken past the point where it repays — which is why none of them can be called wrong, and why §138 forbids teaching any as mandatory. What makes a codebase bad is not the column it started in but the absence of anyone asking whether the structure still matches the changes arriving. The right comparison to make is between your current structure and your last thirty changes, not between two names on a page.