
Why I Ditched PostgreSQL for MongoDB as a Self-Funded Startup Founder
😓 PostgreSQL Broke Me (and My Burn Rate)
Let’s be honest. PostgreSQL is powerful, structured, and has a loyal fanbase that will fight you on Twitter. But as a solo founder trying to build an MVP in 3 months with zero funding and too much caffeine... Postgres felt like a controlling relationship.
Here’s the pain I went through before switching to MongoDB—and why I never looked back.
🧱 PostgreSQL: Rock Solid but Rigid
PostgreSQL is like that super-strict professor. Precise. Demands structure. Doesn’t care if your app logic isn't fully figured out yet.
💢 Here’s What Made Me Cry:
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Schema Hell:
Early-stage startups pivot every 2 weeks. Adding new fields? Migrating?
Postgres said:“Please define this in 17 places, write a migration script, test your types, and pray nothing breaks.”
-
Joins Everywhere:
Joins are great… until you have nested relationships with multiple levels of dependencies.
Suddenly your MVP becomes a dissertation on relational integrity. -
Data Modeling Paralysis:
As a solo dev, I don’t have time to overthink schema design. Postgres made me overengineer from day one. -
Scaling Read Ops?
Great luck with that when you’re figuring out read replicas and connection pooling… with a $0 budget.
🛸 MongoDB: My Agile, Flexible, Startup BFF
Then came MongoDB, the cool kid who let me just get things done.
✅ Why I Switched:
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No Schema, No Cry:
Add new fields? Just do it. MongoDB won’t yell at you. Perfect for building fast and iterating faster. -
One Document = One Thing:
Want to store a user, their cart, and their wishlist together? Do it. Nest away.
It’s like a JSON playground for startup devs. -
Scaling Is Simpler:
Built-in replication, easy sharding, and horizontal scaling meant I could grow without sweating over infra early. -
Free Tier That Actually Works:
Atlas’s free tier is legit. Enough to host my MVP without hitting limits in week 2.
💡 Real-World MVP Pain: My E-Commerce Startup
When I built my first e-commerce MVP:
With PostgreSQL:
- Took 2 weeks just to design the schema for users, addresses, orders, and products.
- Every time we added a new discount rule or variant, we had to write painful migration scripts.
- API speed tanked due to joins across 6 tables.
With MongoDB:
- Designed and deployed my schema in a day.
- Dynamic fields like size/price/variants were just nested objects.
- Orders could evolve on the fly. Versioning? Just store the whole snapshot inside a document.
😎 But Wait—Is MongoDB Perfect?
Nope. It has quirks:
- No joins = More app logic sometimes
- You need to discipline yourself to not over-nest documents
- You can abuse flexibility and regret it later
But for early-stage products where speed > structure, MongoDB wins.
🧘 Founder Philosophy: Move Fast, Then Refactor
I’m not saying you should never use SQL.
When you’re building your final boss version of the product, SQL is great. But during the early chaos stage?
MongoDB lets you ship fast, pivot fast, and sleep at night.
So unless you're funded, staffed, and have a dedicated DB architect, start with something that works with you—not against you.
🚀 Final Verdict
Feature | PostgreSQL | MongoDB |
---|---|---|
Schema Flexibility | ❌ Painful | ✅ Super easy |
MVP Speed | 🐢 Slow | 🏎️ Fast |
Scaling | ⚠️ Complex early | ✅ Built-in |
Learning Curve | ⛰️ Steep | 🛼 Smooth |
Ideal for MVPs | ❌ Meh | ✅ Absolutely |
❤️ Dear SQL Fanboys...
I still love Postgres. I’ll use it again when my startup scales. But for now, as a sleep-deprived, money-starved, solo founder—MongoDB is my ride or die.
💡 Tip: Use what helps you ship. Everything else can be optimized later.
Happy coding, and may your DB never return undefined
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