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.
Simple vs Easy
The pair is repeated as a slogan with an obvious moral — simple good, easy bad — and that reading loses the whole point, which is that they are *independent axes*. Something can be simple and unfamiliar: a data-oriented core with explicit effects at the edges is objectively fewer braided concerns and is harder for a team that has only written service classes. Something can be easy and complex: an ORM that makes the first query one line while braiding together persistence, identity, caching, lazy loading and transaction lifetime behind an attribute. The mistake teams make in one direction is choosing the familiar thing repeatedly until nothing can be reasoned about locally; the mistake in the other direction is imposing a genuinely simpler design on a team that will not be able to maintain it, which is a real cost that simplicity advocates tend to wave away. The useful move is to name which axis you are arguing on. "This is hard for us" is a legitimate objection about the team and can be answered with time, examples and pairing. "This braids four concerns" is an objection about the artefact, and no amount of familiarity fixes it.
When the code will be read, changed and debugged for years by people who were not there. Simplicity is what keeps the cost of the tenth change close to the cost of the first.
When the horizon is short, the team is small and known, or the friction of the unfamiliar would genuinely cost more than the interleaving. Easy is a real value, not a vice.
| Dimension | Simple — few interleaved concerns; one thing, not braided together | Easy — near at hand; familiar, quick to start with, low friction today |
|---|---|---|
| A property of | The artefact | The relationship between the artefact and this team, today |
| Measured by | How many concerns are interleaved in one place | How quickly someone gets started |
| Changes over time | Only if you change the design | Yes — familiarity is learnable |
| Pays off | On the tenth change, and on the incident at 3am | On the first day, and on the deadline this week |
| Typical seduction | Purity for its own sake, imposed on people who did not choose it | A one-line API that hides four decisions you will later need |
| Right objection to raise | "This braids persistence into the rule" | "Nobody here has used this and we ship on Thursday" |
| How to answer it | Separate the concerns, or accept the cost explicitly | Pairing, examples, time — or choose the familiar thing on purpose |
| Are they opposed | No — they are independent, and the best designs are both | No — but when they conflict, say which axis you are arguing on |
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.