The Problem I Wanted to Solve
Static diagrams don’t age well. A database evolves, but a hand-drawn ERD doesn’t.
I wanted something that:
Worked with both live PostgreSQL connections and plain SQL DDL files.
Produced diagrams that were accurate every time I ran it.
Looked clean enough to use in onboarding docs or architecture reviews.
In short: an automated PostgreSQL schema visualization tool that removed guesswork and made database exploration easier.
The Technical Journey
I started with Python, because it has two powerful libraries that solved 80% of the problem:
SQLAlchemy for reflecting database schemas and relationships.
Graphviz for rendering crisp, customizable diagrams.
But the real challenge was parsing raw PostgreSQL DDL. PostgreSQL syntax is flexible, sometimes messy. Comments, nested parentheses, table-level constraints, and custom types all had to be handled.
I built a parser that:
Cleans comments and procedural blocks.
Extracts primary keys, foreign keys, constraints, and defaults.
Supports complex relationships like multi-column foreign keys.
The payoff: whether you give the tool a schema.sql file or point it at a database URL, the output is the same — a complete, accurate Entity Relationship Diagram.
Making the Output Useful
A diagram is only as good as its readability. I designed the visuals to highlight what developers care about:
🔑 Primary keys with clear icons.
🔗 Foreign key relationships with arrows.
Data types and default values right under each column.
Optional schema names in headers for multi-schema projects.
Users can also customize:
Format: SVG, PNG, or PDF.
Layout: left-to-right or top-to-bottom.
Scope: include or exclude schemas to keep the diagram focused.
The goal was to make the defaults smart but still give advanced users control.
The Outcome
The PostgreSQL Visualizer turned into more than just a utility.
It became a way to:
Onboard new developers faster.
Keep architectural documentation in sync.
Save hours of schema exploration when starting a new project.
For me, it also reinforced an important principle: tools should eliminate friction. By automating what used to be a tedious task, this project freed me to focus on design and problem-solving — not detective work.
Takeaway
Building the PostgreSQL Visualizer taught me that the best developer tools aren’t just technical. They solve a human problem: communication.
Now, instead of wrestling with database schemas, I can generate a diagram with one command.
And that’s clarity worth building.
Check it out on my Github!
The Problem I Wanted to Solve
Static diagrams don’t age well. A database evolves, but a hand-drawn ERD doesn’t.
I wanted something that:
Worked with both live PostgreSQL connections and plain SQL DDL files.
Produced diagrams that were accurate every time I ran it.
Looked clean enough to use in onboarding docs or architecture reviews.
In short: an automated PostgreSQL schema visualization tool that removed guesswork and made database exploration easier.
The Technical Journey
I started with Python, because it has two powerful libraries that solved 80% of the problem:
SQLAlchemy for reflecting database schemas and relationships.
Graphviz for rendering crisp, customizable diagrams.
But the real challenge was parsing raw PostgreSQL DDL. PostgreSQL syntax is flexible, sometimes messy. Comments, nested parentheses, table-level constraints, and custom types all had to be handled.
I built a parser that:
Cleans comments and procedural blocks.
Extracts primary keys, foreign keys, constraints, and defaults.
Supports complex relationships like multi-column foreign keys.
The payoff: whether you give the tool a schema.sql file or point it at a database URL, the output is the same — a complete, accurate Entity Relationship Diagram.
Making the Output Useful
A diagram is only as good as its readability. I designed the visuals to highlight what developers care about:
🔑 Primary keys with clear icons.
🔗 Foreign key relationships with arrows.
Data types and default values right under each column.
Optional schema names in headers for multi-schema projects.
Users can also customize:
Format: SVG, PNG, or PDF.
Layout: left-to-right or top-to-bottom.
Scope: include or exclude schemas to keep the diagram focused.
The goal was to make the defaults smart but still give advanced users control.
The Outcome
The PostgreSQL Visualizer turned into more than just a utility.
It became a way to:
Onboard new developers faster.
Keep architectural documentation in sync.
Save hours of schema exploration when starting a new project.
For me, it also reinforced an important principle: tools should eliminate friction. By automating what used to be a tedious task, this project freed me to focus on design and problem-solving — not detective work.
Takeaway
Building the PostgreSQL Visualizer taught me that the best developer tools aren’t just technical. They solve a human problem: communication.
Now, instead of wrestling with database schemas, I can generate a diagram with one command.
And that’s clarity worth building.
Check it out on my Github!
