COBOL vs SQL vs MONGODB

Three Decades • Three Paradigms • One Mission

⚡ THE MISSION

This project showcases how the SAME database operations look in THREE fundamentally different technologies, spanning from 1959 to 2009. Witness the evolution of data management through working code examples.

📅 TIMELINE OF INNOVATION

1959

COBOL

Procedural
File Processing

1974

SQL

Declarative
Relational Model

2009

MONGODB

Document
NoSQL

1959

COBOL

Philosophy: Tell the computer EXACTLY what to do

Data Model: Fixed-length records in files

Approach: Procedural, step-by-step control

Best For: Batch processing, mainframe systems

EXPLORE COBOL →
1974

SQL

Philosophy: Describe WHAT you want, not HOW

Data Model: Tables with relations

Approach: Declarative, set-based operations

Best For: Relational data, ACID guarantees

EXPLORE SQL →
2009

MONGODB

Philosophy: Flexible, developer-friendly

Data Model: JSON-like documents

Approach: Schema-less, embedded data

Best For: Rapid development, horizontal scale

EXPLORE MONGODB →

📊 BY THE NUMBERS

Operation COBOL Lines SQL Lines MongoDB Lines
Create Record 11 2 7
Find by ID 9 2 1
Search by Criteria 14 3 2
Calculate Average 12 1 10
Update Record 12 2 4

🎓 WHAT YOU'LL LEARN

Different Paradigms

See how procedural, declarative, and document-oriented approaches solve the same problems differently.

Data Models

Understand fixed records, relational tables, and flexible documents through practical examples.

Trade-offs

Learn when to use each technology based on your specific requirements.

Historical Context

Discover why each technology emerged and the problems it was designed to solve.

🚀 GET STARTED

All examples are designed to run with MINIMAL infrastructure. No mainframes, no cloud accounts, no complex setup!

💻 EXAMPLES ⚖️ COMPARISON 🚨 ANTI-PATTERNS 💎 CONCLUSIONS

This project is open source and hosted on GitHub. Download all the code, run the examples locally, and explore three generations of database technology.

📦 DOWNLOAD FROM GITHUB

✨ PROJECT HIGHLIGHTS