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.
Package by layer vs Package by feature
The layer layout is defended as "separation of concerns", and that is the confusion: it separates *technical kinds*, not concerns. A concern is something that changes for one reason, and no requirement anyone has ever filed was about controllers. The test is mechanical — open the last thirty merged changes and see how many directories each touched. If the typical feature edits four directories and owns none, the folders are organising code by what it is made of rather than by what it is about, which means every change is a shotgun change and nothing can be deleted with confidence. The counter-argument deserves stating properly, though, because feature folders are not free: layers give you an obvious, uniform place to put a new file, and a junior engineer never has to decide anything; feature folders require someone to decide what a feature is, they leak when a capability is genuinely cross-cutting, and they tempt each slice into reimplementing shared infrastructure. In practice most healthy large codebases are feature-first with a thin, deliberately boring platform layer underneath, and the mistake is treating the layer names inside a feature as if they were the top-level structure.
Small codebases where the whole thing fits in one head, teaching contexts where the layering is the lesson, and frameworks that impose the layout so hard that fighting it costs more than it saves.
Anything where features are added and removed as units, where teams own capabilities rather than tiers, and where you want the build to be able to say "notifications may not import billing internals".
| Dimension | By layer — controllers/, services/, repositories/, models/ | By feature — billing/, subscriptions/, notifications/, each containing its own layers |
|---|---|---|
| Top-level directories mean | Technical kind of file | Business capability |
| A typical change touches | Every layer directory, part of none | One directory, usually one team |
| Deleting a feature | Hunt through four folders and hope | Delete the folder |
| Enforceable boundaries | Hard — layers are not ownership lines | Natural — module visibility rules apply per feature |
| Where a new file goes | Obvious, always | Requires a judgement about which feature owns it |
| Cross-cutting concerns | Fit the layout naturally | Awkward; need a deliberate shared platform area |
| Risk | Every change is a shotgun change | Slices duplicating infrastructure, or a shared/ folder growing back |
| Scales with | Number of layers, which is fixed | Number of features and teams, which is what actually grows |
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.