Self-Hosted Database Diagram & Design Tools: DrawDB vs ChartDB vs Azimutt Compared

Introduction

Before writing a single line of SQL, database architects and developers need to visualize their schema. Entity-Relationship (ER) diagrams, table relationship maps, and schema documentation are essential for designing new databases, understanding existing ones, and communicating data models across teams. While traditional desktop tools like MySQL Workbench and pgAdmin offer basic diagramming, modern web-based tools provide collaborative, always-available schema visualization that integrates directly with your development workflow.

This article compares three leading self-hosted database diagram tools: DrawDB, ChartDB, and Azimutt. Each takes a different approach to the fundamental challenge of making database schemas visible, understandable, and maintainable.

Comparison Table

Deep Dive: Architecture and Capabilities

DrawDB

DrawDB is a free, web-based database diagram editor with an intuitive drag-and-drop interface. Its primary strength is the manual design workflow — you can visually lay out tables, define columns, set data types, and establish foreign key relationships entirely through the UI. DrawDB then generates the corresponding SQL DDL statements, which you can export and execute against your database.

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# docker-compose.yml for DrawDB
version: "3.8"
services:
  drawdb:
    image: ghcr.io/drawdb-io/drawdb:latest
    ports:
      - "3000:80"
    restart: unless-stopped

DrawDB’s standout features include:

• Visual table designer: Add columns with types, defaults, constraints
• Relationship builder: Drag between tables to create foreign keys
• Multi-database support: Generates correct DDL syntax for each database
• Import/Export: Import existing SQL schemas, export diagrams as images or SQL
• Template library: Pre-built schema templates for common use cases

ChartDB

ChartDB takes a unique approach: instead of manually designing diagrams, you connect to your database and run a single query. ChartDB automatically discovers all tables, columns, and relationships, generating a complete ER diagram from your live schema. This makes it exceptionally fast for understanding existing databases — particularly large, poorly-documented ones.

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# docker-compose.yml for ChartDB
version: "3.8"
services:
  chartdb:
    image: ghcr.io/chartdb/chartdb:latest
    ports:
      - "3001:8080"
    environment:
      - DATABASE_URL=postgresql://user:pass@host:5432/db
    restart: unless-stopped

ChartDB is ideal for:

• Reverse engineering: Instantly visualize any database with one query
• Schema auditing: Quickly spot missing indexes, orphan tables, or inconsistent naming
• Onboarding: New team members can understand the data model in minutes
• Documentation: Export diagrams for architecture decision records

Azimutt

Azimutt positions itself as a “database exploration and documentation” tool rather than a pure diagramming tool. It connects directly to your database and provides multiple ways to explore the schema: an ER diagram, a searchable table list, column-level documentation, and relationship navigation. Azimutt is particularly strong at handling large, complex schemas with hundreds of tables.

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# docker-compose.yml for Azimutt
version: "3.8"
services:
  azimutt:
    image: azimuttapp/azimutt:latest
    ports:
      - "3002:4000"
    environment:
      - DATABASE_URL=ecto://user:pass@host/db
      - SECRET_KEY_BASE=your-secret-key
      - HOST=localhost
    restart: unless-stopped

Azimutt’s key differentiators:

• Schema-wide search: Find any table, column, or relationship instantly
• Documentation annotations: Add notes, descriptions, and tags to tables and columns
• Relationship explorer: Navigate foreign key chains across multiple tables
• Layout persistence: Diagram layouts are saved and shared across your team
• API-driven: REST API for programmatic schema access

Choosing the Right Tool

• Choose DrawDB if you are designing new databases from scratch and want full control over the visual layout. Its manual design interface and template library make it the best choice for greenfield projects where you want to plan the schema before implementing it.

• Choose ChartDB if you need to quickly understand existing, potentially undocumented databases. The single-query auto-discovery is unmatched for reverse engineering, schema auditing, and developer onboarding.

• Choose Azimutt if you are working with large, complex schemas (100+ tables) and need a documentation platform, not just a diagram. Its search, annotation, and API capabilities make it more of a “database knowledge base” than a simple drawing tool.

Why Self-Host Your Database Design Tools?

Security and compliance: Database schemas often reveal sensitive business logic — table structures expose your data model, which is proprietary intellectual property. Self-hosting keeps schema information within your network rather than on a third-party cloud service. For regulated industries, this is often a hard requirement.

Always-available documentation: Cloud services go down, change pricing, or discontinue features. Self-hosted tools ensure your schema documentation is always accessible — even during internet outages or when working from restricted networks. The documentation lives alongside your infrastructure.

Integration with development workflows: Self-hosted tools can be integrated into CI/CD pipelines, deployed alongside development environments, and accessed via internal URLs. Azimutt’s REST API, for example, enables automated schema documentation updates as part of your deployment pipeline.

For teams working with SQL query tools, our web-based SQL editor comparison covers platforms that pair naturally with diagram tools. If you need schema documentation generation, our guide on database schema documentation tools covers automated documentation generators. For broader database management, check out our self-hosted database GUI comparison.

Integrating Diagrams into Your Development Workflow

Here’s how these tools fit into a modern database development workflow:

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┌──────────────┐     ┌──────────────┐     ┌───────────────┐
│  Design      │────▶│  Implement   │────▶│  Document     │
│  (DrawDB)    │     │  (Migration) │     │  (Azimutt)    │
└──────────────┘     └──────────────┘     └───────┬───────┘
                                                  │
                    ┌─────────────────────────────┤
                    │                             │
              ┌─────▼──────┐              ┌──────▼──────┐
              │  Review     │              │  Onboard     │
              │  (ChartDB)  │              │  (Azimutt)   │
              └────────────┘              └─────────────┘

1. Design phase: Use DrawDB to sketch out your schema visually, get team feedback, and export the DDL
2. Implementation phase: Apply migrations to your development database
3. Review phase: Use ChartDB to auto-generate a diagram of the implemented schema and compare it to the design
4. Document phase: Use Azimutt to maintain living documentation that stays in sync with the database
5. Onboarding: New team members start with Azimutt’s search and exploration features to understand the schema

Performance and Scalability

For small to medium databases (under 100 tables), all three tools perform well with minimal resources. DrawDB stores everything in the browser’s local storage, so performance depends on the client machine. ChartDB and Azimutt query the database directly, so performance depends on database responsiveness and schema complexity.

For large databases (200+ tables), Azimutt is the strongest performer because it was designed specifically for this use case. Its schema parser handles complex relationships efficiently, and the UI remains responsive even with thousands of columns. ChartDB’s auto-discovery can be slower on very large schemas because it analyzes all relationships in a single pass.

FAQ

Do I need to install anything on the database server?

No. All three tools connect to your database remotely using standard connection strings. DrawDB does not connect to databases at all — it imports from SQL files. ChartDB needs read-only access to your information_schema or system catalog. Azimutt needs read-only access to your database schema. None of them modify your data or schema without explicit action.

Can I export diagrams to embed in documentation or wikis?

Yes. DrawDB exports to PNG and SVG for image embedding. ChartDB exports to PNG, SVG, and PDF. Azimutt generates markdown documentation that can be embedded in wikis and static site generators. All three produce standard formats suitable for architecture decision records and internal documentation.

How do these compare to schema migration tools like Liquibase or Flyway?

Schema diagram tools and migration tools serve different purposes. Diagram tools visualize and document your current schema. Migration tools manage schema changes as version-controlled scripts. They are complementary: use DrawDB or ChartDB to design and understand your schema, and use Liquibase or Flyway to deploy changes reliably. Azimutt can serve as the documentation layer that stays current between migrations.

Are there desktop alternatives with more features?

Yes. DBeaver (free, multi-database) and DataGrip (paid, JetBrains) both include ER diagram features alongside full SQL editing capabilities. pgModeler is a dedicated PostgreSQL modeling tool with extensive features. However, desktop tools lack the collaborative, always-available nature of web-based tools — diagrams live on individual machines rather than being accessible to the whole team.

Can I use these tools for NoSQL databases?

Primarily not. These tools are designed for relational databases with defined schemas (tables, columns, foreign keys). Document databases like MongoDB, key-value stores like Redis, and graph databases like Neo4j have fundamentally different data models that these tools do not support. For NoSQL schema visualization, you would need database-specific tools like MongoDB Compass or Neo4j Browser.

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