DETAILED COMPARISON

COBOL: Fixed Records

01  EMPLOYEE-RECORD.
    05 EMP-ID               PIC X(4).
    05 EMP-FIRST-NAME       PIC X(20).
    05 EMP-LAST-NAME        PIC X(20).
    05 EMP-DEPARTMENT       PIC X(15).
    05 EMP-SALARY           PIC 9(7)V99.
    05 EMP-HIRE-DATE        PIC X(10).

* Every record = EXACTLY 78 bytes
* Fixed at compile time
* No optional fields
* Change requires recompilation

SQL: Tables with Schema

CREATE TABLE employees (
    id          VARCHAR(4) PRIMARY KEY,
    first_name  VARCHAR(20) NOT NULL,
    last_name   VARCHAR(20) NOT NULL,
    department  VARCHAR(15) NOT NULL,
    salary      DECIMAL(9,2) CHECK (salary >= 0),
    hire_date   DATE NOT NULL
);

-- Constraints enforced
-- Nullable vs NOT NULL
-- Change via ALTER TABLE

MongoDB: Flexible Documents

{
    _id: "E001",
    firstName: "John",
    lastName: "Smith",
    department: "Engineering",
    salary: 85000,
    hireDate: ISODate("2020-01-15"),
    skills: ["Java", "Python"],     // Optional!
    contact: {                       // Nested!
        email: "[email protected]"
    }
}

// Each document can differ
// No fixed schema
// Add fields anytime

COBOL Approach: Sequential Scan

PERFORM UNTIL WS-EOF
    READ EMPLOYEE-FILE NEXT RECORD
        AT END SET WS-EOF TO TRUE
        NOT AT END
            IF EMP-DEPARTMENT = "Engineering"
                AND EMP-SALARY > 80000
                DISPLAY EMP-ID " - " EMP-FIRST-NAME
            END-IF
    END-READ
END-PERFORM.

✓ Complete control
✗ Must scan entire file
✗ Manual loop logic

SQL Approach: Declarative Query

SELECT id, first_name, last_name, salary
FROM employees
WHERE department = 'Engineering'
  AND salary > 80000
ORDER BY salary DESC;

✓ Concise syntax
✓ Automatic optimization
✓ Index usage

MongoDB Approach: Query Document

db.employees.find({
    department: "Engineering",
    salary: { $gt: 80000 }
}).sort({ salary: -1 })

✓ Rich operators
✓ Chainable methods
✓ Automatic index usage