惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

V
Visual Studio Blog
罗磊的独立博客
小众软件
小众软件
T
Tailwind CSS Blog
宝玉的分享
宝玉的分享
博客园_首页
N
Netflix TechBlog - Medium
B
Blog
Recent Announcements
Recent Announcements
Y
Y Combinator Blog
Blog — PlanetScale
Blog — PlanetScale
L
LangChain Blog
F
Fortinet All Blogs
The GitHub Blog
The GitHub Blog
Stack Overflow Blog
Stack Overflow Blog
C
Check Point Blog
Last Week in AI
Last Week in AI
Jina AI
Jina AI
V
V2EX
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - 叶小钗
博客园 - 【当耐特】

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
When should you stop using Google Sheets as your backend?
Yodsavee Sup · 2026-05-14 · via DEV Community

When should you stop using Google Sheets as your backend?

In my last post, I wrote about why many MVPs start with Google Sheets.

It is fast, familiar, and easy for non-technical people to update.

But there is an important follow-up question:

When should you stop using Google Sheets as your backend?

Because the answer is not “never use Sheets.”

And it is also not “use Sheets forever.”

Google Sheets can be a great starting point, but it should not become an accidental permanent architecture.

Google Sheets is good when speed matters most

For an early MVP, Google Sheets can be useful because:

  • the schema is still changing
  • the product idea is not fully validated yet
  • non-technical teammates need to edit data
  • you do not want to build an admin panel too early
  • you need a quick demo or prototype
  • the traffic is still low

At this stage, the goal is not perfect infrastructure.

The goal is learning.

Can users understand the product?
Does the workflow make sense?
Is this worth building further?

For that stage, a spreadsheet can be enough.

The warning signs

The problems usually start when the spreadsheet becomes part of a real product workflow.

Here are signs that your Google Sheets setup is reaching its limit.

1. Your frontend needs reliable API access

If your app needs to read data from Sheets regularly, you probably need a proper API layer.

Directly depending on spreadsheet structure can become fragile.

Columns change.
Tabs get renamed.
Data types are inconsistent.
Permissions become unclear.

At this point, the app should not depend directly on the sheet.

It should depend on an API contract.

2. Multiple people need different permissions

Google Sheets permissions are simple, but app permissions are usually more specific.

You may need:

  • admin access
  • read-only users
  • client access
  • team access
  • API key access
  • restricted rows or tables

Once permissions become more detailed, the spreadsheet alone is not enough.

3. Data validation starts breaking

Spreadsheets are flexible.

That is both a strength and a weakness.

Someone can type yes, TRUE, active, or 1 to mean the same thing.

Someone can delete a column.
Someone can leave required fields empty.
Someone can paste malformed data.

If your app depends on clean data, validation needs to move into a more controlled layer.

4. Usage grows beyond simple traffic

Google Sheets is not designed to be a high-performance backend.

For low-to-medium traffic apps, it can work with caching and guardrails.

But if your app needs high request volume, complex queries, transactions, or low latency, it is time to move to a real database.

5. Migration becomes harder every week

This is one of the biggest risks.

A spreadsheet MVP is fine.

But if your app is tightly coupled to spreadsheet-specific logic, migration becomes painful later.

That is why I think the frontend should talk to an API, not directly to the sheet.

Today, the API can be powered by Google Sheets.

Later, it can be powered by Postgres or another database.

The API contract gives you a cleaner migration path.

A simple rule

Here is how I think about it:

Use Google Sheets when you are still validating the workflow.

Move beyond Sheets when reliability, permissions, performance, or data integrity become more important than speed.

In other words:

Google Sheets is great for learning.
A real database is better for scaling.
An API layer helps bridge the two.

Enter fullscreen mode Exit fullscreen mode

The middle stage

The interesting part is the middle stage.

This is where many MVPs, internal tools, and client portals live.

They are not just prototypes anymore.

But they also do not need complex infrastructure yet.

They need:

  • a REST API
  • a dashboard
  • API keys
  • permissions
  • caching
  • usage limits
  • validation
  • a future migration path

That is the stage I’m building for with TarangDB.

The idea is not to replace Postgres, Supabase, Firebase, or a real database.

The idea is to make the early stage smoother:

Start with Google Sheets.
Add a backend layer around it.
Ship faster.
Move to a real database when the product actually needs it.

My current thinking

Google Sheets should not be treated as the final backend for every product.

But it also should not be dismissed too early.

For many teams, it is the fastest way to start.

The important thing is to avoid getting trapped.

A spreadsheet can be the starting point.

The API contract should be the bridge.

The database can come later.

Question for builders

Have you ever used Google Sheets, Airtable, or a spreadsheet-like tool as the backend for an MVP or internal tool?

What made you stop using it?

Was it:

  • permissions
  • performance
  • data validation
  • API access
  • collaboration
  • migration
  • something else?

Quick demo

Here is a short demo of the idea:

I’d love to hear real examples.