Archynt vs Structurizr
Structurizr is the canonical C4 tool, written by the person who invented C4. This page is about one specific difference: where the model comes from.
Structurizr was created by Simon Brown, the author of the C4 model itself. It is not a competitor we can wave away as a diagramming toy — it is the reference implementation of the notation Archynt also produces, with a mature DSL, a CLI, ADR support and a community that has been modelling systems with it for years. If you already model in Structurizr and it works, this page is probably not going to convince you to stop, and it isn't trying to.
Where Structurizr is strong
Because the model is written by hand, you can model anything. A system you have no source access to. A third-party SaaS your platform depends on. Next year's target architecture that doesn't exist yet. The boundary you want teams to respect. None of that is derivable from a codebase, because none of it is in the codebase — and all of it is legitimate architectural work.
You also get total control over what each diagram shows. A derived diagram gives you what's there, which is frequently more than a reader needs; a hand-authored view gives you exactly the seven boxes that make the point. For a diagram whose job is to communicate to humans, that curation is a feature, not a limitation.
And Structurizr Lite is free and open source, runs as a Docker container, and is genuinely enough for one person authoring a model. That's hard to beat on cost.
Where the two diverge
A hand-authored model asserts. Nothing checks it. The DSL says the payments service talks to the ledger, and it will keep saying that after someone deletes the call, after someone adds an undocumented dependency on the fraud service, and after the whole thing is refactored. The model is correct on the day it's written and degrades quietly from then on, at a rate nobody can measure — because measuring it would mean comparing the model to the system, which is the work the model was supposed to save you.
Archynt inverts that. It parses the repository into a structural graph, runs a read-only agent that observes what actually talks to what, and tags every dependency as static, runtime, or both. The C4 diagram is a projection of that graph rather than a document maintained alongside it, so the failure mode of a stale diagram doesn't exist. When code and runtime disagree, that disagreement is the finding — a call in production no code path explains, or a dependency in the code the runtime never exercises.
| Capability | Archynt | Structurizr |
|---|---|---|
| C4 model diagrams | ||
| Where the model comes from | Derived from code + runtime | Hand-authored DSL |
| Verified against the running system | ||
| Architectural drift detection | ||
| Model intended or future-state architecture | ||
| Diagram a system you have no source for | ||
| ADRs and long-form documentation authoring | ||
| Deployment views | From live runtime | Hand-authored |
| PR/CI architectural gate | ||
| MCP server for AI coding agents | ||
| Language coverage | Java, Node, Python, Go | Any — the model is manual |
| Free option | Free tier | Structurizr Lite, open source |
These are more complementary than competitive
The honest framing is that Structurizr answers "what should this system look like" and Archynt answers "what does it actually look like right now." Those are different questions and mature teams need both. If you're doing design work — proposing a decomposition, communicating a target state, writing ADRs — use Structurizr, and use Lite, because it's free and it's very good at that.
Where we'd argue for Archynt is the maintenance problem: if the reason your diagrams are wrong is that keeping them right is somebody's unpaid side job, no DSL fixes that, because the DSL is the side job. That's the case we built for.
Want to see this on your own system?
A repository URL is enough for the static graph. The runtime agent takes one docker-compose file.
