gjalla vs Structurizr: Which Architecture Tool Fits Your Team?

Both gjalla and Structurizr solve the same fundamental problem: making software architecture visible and understandable. But they take fundamentally different approaches. This comparison will help you decide which fits your team’s workflow.

The Core Difference

Structurizr is architecture-as-code. You write a DSL (Domain Specific Language) that describes your system, and Structurizr renders it as C4 diagrams.

gjalla is architecture-from-code. You connect your repository, and gjalla analyzes your actual codebase to generate living documentation.

This isn’t a subtle distinction. It determines who maintains the documentation, how accurate it stays, and what happens when your system evolves.

How Each Tool Works

Structurizr’s Approach

With Structurizr, you define your architecture in the Structurizr DSL:

workspace {
    model {
        user = person "User"
        softwareSystem = softwareSystem "My System" {
            webapp = container "Web Application"
            database = container "Database"
        }
        user -> webapp "Uses"
        webapp -> database "Reads from"
    }
    views {
        systemContext softwareSystem {
            include *
            autolayout lr
        }
    }
}

This generates C4 diagrams at multiple levels: System Context, Container, Component, and Deployment views. The DSL lives in your repo, version-controlled alongside your code.

gjalla’s Approach

With gjalla, you install a GitHub app and point it at your repository. gjalla:

1. Analyzes your actual source code
2. Identifies services, databases, APIs, and their relationships
3. Generates interactive architecture diagrams
4. Updates automatically when your code changes

No DSL to write. No manual sync required.

Comparison Table

Aspect	Structurizr	gjalla
Source of truth	DSL file you maintain	Your actual codebase
Initial setup	Write DSL describing your system	Connect repo, wait for analysis
Ongoing maintenance	Update DSL when architecture changes	Automatic with code changes
Accuracy guarantee	Only as accurate as your DSL	Reflects actual implementation
C4 model support	Native, full support	Generates equivalent views
Learning curve	Learn Structurizr DSL	None (just connect repo)
Customization	Full control over diagram layout	AI-optimized layouts
ADR support	Built-in	Built-in
Data flow tracing	Manual definition	Automatic detection
AI agent integration	Export diagrams	Native MCP server for agents

When Structurizr Works Best

Structurizr excels when:

• You’re designing before building. Structurizr is excellent for upfront architecture design. You can model a system that doesn’t exist yet.

• You need precise control over diagrams. Every element, every relationship, every view is explicitly defined. Nothing appears that you didn’t specify.

• Your architecture is stable. If your system changes infrequently, keeping the DSL in sync is manageable.

• You’re standardizing on C4. Structurizr was created by Simon Brown, who developed the C4 model. It’s the reference implementation.

• You have dedicated architecture time. Someone needs to maintain the DSL. If your team has that capacity, Structurizr delivers excellent results.

When gjalla Works Best

gjalla excels when:

• AI is writing your code. When Cursor, Copilot, or other agents are making changes, you can’t manually track every architectural decision. gjalla watches what actually ships.

• Your system evolves rapidly. Startups, greenfield projects, and teams shipping daily can’t maintain a separate DSL. gjalla stays current automatically.

• You need to understand an existing system. Joining a new team? Inheriting a codebase? gjalla shows you what’s actually there, not what someone documented years ago.

• Documentation keeps drifting. If your architecture diagrams are perpetually out of date, gjalla eliminates the maintenance burden.

• You want AI agents to understand your system. gjalla’s MCP server provides architectural context directly to coding agents, helping them make better decisions.

The Architecture Drift Problem

This is the fundamental tension between the two approaches.

With Structurizr, your DSL is a model of your system. Models drift from reality unless someone actively maintains them. Every time a developer adds a new service, changes a database, or refactors an API, someone needs to update the DSL.

In practice, this maintenance often doesn’t happen. The DSL falls behind. Diagrams become aspirational rather than accurate. New team members learn the wrong mental model.

gjalla sidesteps this entirely. There’s no model to maintain because the documentation comes from the code itself. When the code changes, the documentation changes.

Can You Use Both?

Yes. They serve complementary purposes:

• Use Structurizr for target-state architecture, design proposals, and formal C4 documentation that needs precise control.
• Use gjalla for current-state visibility, onboarding, impact analysis, and keeping AI agents aligned.

Some teams use Structurizr for the architecture they’re building toward, and gjalla to see what they’ve actually built.

Making the Decision

Ask yourself:

1. Who will maintain the documentation? If you have dedicated architecture capacity, Structurizr works well. If not, gjalla removes the burden.

2. How fast is your system changing? Rapid change favors gjalla. Stable systems can use either.

3. Do you need to design before you build? Structurizr excels here. gjalla documents what exists.

4. Are AI agents writing your code? gjalla was built for this world. It watches what ships, not what was planned.

5. Is your current documentation accurate? If your diagrams are always out of date, that’s a signal that manual maintenance isn’t working.

Conclusion

Structurizr and gjalla represent two philosophies of architecture documentation:

• Structurizr: Architecture is an artifact you create and maintain, separate from the code.
• gjalla: Architecture is a view of the code itself, generated and updated automatically.

Neither is universally better. Structurizr gives you control and precision. gjalla gives you accuracy and zero maintenance.

For teams building with AI coding agents, where the system evolves faster than humans can document, gjalla’s approach becomes essential. You can’t maintain a DSL when you’re reviewing dozens of AI-generated pull requests per day.

The question isn’t which tool is better. It’s which approach matches how your team actually works.