easyFull Stack EngineerSaaS
What are the key differences between SQL and NoSQL databases? When would you choose MongoDB over PostgreSQL?
Posted 18/04/2026
by Mehedy Hasan Ador
Question Details
At a startup interview, the CTO asked:
> "We're building a SaaS platform with user profiles, job applications, and analytics. We need flexibility in our data model because we're iterating fast. Should we use PostgreSQL or MongoDB? What are the trade-offs?"
> "We're building a SaaS platform with user profiles, job applications, and analytics. We need flexibility in our data model because we're iterating fast. Should we use PostgreSQL or MongoDB? What are the trade-offs?"
Suggested Solution
SQL vs NoSQL Comparison
When to Choose MongoDB
// Flexible schema — iterate fast
const jobApplication = {
company: "Google",
position: "SWE",
customFields: { // No migration needed to add fields
referral: "John",
source: "LinkedIn",
},
interviewRounds: [ // Embed arrays directly
{ round: 1, type: "phone", feedback: "..." },
{ round: 2, type: "onsite", feedback: "..." },
],
};
When to Choose PostgreSQL
-- Complex relational queries
SELECT u.name, COUNT(a.id) as applications, AVG(a.salary) as avgsalary
FROM users u
JOIN applications a ON u.id = a.userid
JOIN companies c ON a.companyid = c.id
WHERE c.industry = 'fintech'
GROUP BY u.id
HAVING COUNT(a.id) > 5
ORDER BY avgsalary DESC;
Hybrid Approach (Common in Production)
MongoDB → User-generated content, logs, analytics, flexible data
PostgreSQL → Financial records, user accounts, complex reporting
Redis → Caching, sessions, rate limiting
MongoDB Strengths for Interview OS
1. Flexible question data: Tags, sketchData (JSON), optional fields — no migrations2. Embedded documents: Interview rounds inside applications
3. Horizontal scaling: Sharding for high write throughput
4. JSON native: Direct storage of JS objects, no ORM mapping friction
PostgreSQL Strengths
1. Complex JOINs: Reporting across users, applications, companies2. Data integrity: Foreign keys, constraints, triggers
3. Full-text search: Built-in tsvector
4. Analytics: Window functions, CTEs, materialized views