The Indie Dev’s Database Dilemma: PostgreSQL vs. MongoDB vs. Supabase in 2026

If you’ve ever launched a new app idea—a SaaS platform, a niche productivity tool, or a clever utility—you know the feeling. That paralyzing moment of analysis paralysis when you stare at the database selection screen.

It feels like choosing the foundation of a skyscraper before you've even finished the napkin sketch. Pick wrong, and you might spend a month down the line rewriting expensive migration scripts or debugging frustrating consistency issues.

Frankly, choosing a database is the highest-leverage decision you make early on. It affects everything: your development speed, your security model, and crucially, your future scaling costs.

For years, the debate was simple: SQL (Postgres, MySQL) vs. NoSQL (MongoDB, Cassandra). But for us solo and small-team indie developers, the landscape has changed dramatically. The introduction and maturity of force multipliers—Backend as a Service (BaaS) solutions like Supabase—have thrown a massive wrench into the mix.

I've used all three extensively in production apps, and I’m here to give you the honest, pragmatic breakdown. Let’s cut the theoretical academic nonsense and talk about what actually gets apps shipped in 2026.

TL;DR: For the vast majority of modern, full-stack indie applications with structured data (users, payments, orders), Supabase (PostgreSQL) is the pragmatic, high-velocity choice due to its instant API, RLS, and Auth integration. You get Enterprise-grade reliability without the DevOps debt ¹.

The Contenders: A High-Level Reality Check

We’re comparing three different philosophies here. Understanding the underlying ethos is key to choosing the right tool for your specific application requirements.

1. PostgreSQL (The Reliable Workhorse)

Postgres is the definition of reliability. It’s mature, feature-rich, ACID-compliant, and beloved by professionals for a reason. When people say, "Start with Postgres unless you have a good reason not to," they’re usually right.

The Indie Reality: Setting up and maintaining a self-managed Postgres cluster (or even a basic managed service like RDS) still requires serious DevOps chops and migration planning. It’s slow to start, but rock-solid once running.

2. MongoDB (The Agile Prototype)

MongoDB pioneered the Document Database revolution, offering incredible schema flexibility. If your data structure changes daily, or if your data naturally fits into giant JSON blobs (like logging data, user preferences), Mongo is fast and easy to prototype with.

The Indie Reality: Mongo can lead to "schema debt." That incredibly cool flexibility feels amazing on Day 1, but when you hit scale and need complex joins or mandatory type-safety, you pay that debt back with interest, often in the form of messy application logic.

3. Supabase (The Force Multiplier BaaS)

Supabase isn't a database type; it's a platform built around Postgres. It packages Postgres with instant, auto-generated REST and GraphQL APIs, real-time subscriptions, user authentication, storage, and even edge functions.

The Indie Reality: This is the ultimate accelerator. It takes the best of Postgres's reliability and wraps it in the developer experience of Firebase or Parse, completely eliminating the need to write 80% of your backend glue code.

Deep Dive: The Developer Experience

When I’m building an app, I measure my tools not by theoretical maximum throughput, but by how many hours they save me this week.

A. The Postgres Path: Unlocking JSONB Magic

I still love raw PostgreSQL for specific projects—especially those requiring complex geospatial queries, or highly customized data warehouse reporting where I need total control over indexes and extensions.

Why it still matters:

1. ACID Compliance: Transactions work perfectly. If I'm building an e-commerce platform or a subscription service where money and inventory are involved, I sleep better knowing Postgres is enforcing consistency.
2. JSONB is the Secret Weapon: This is the most pragmatic feature for indies. Postgres can store schemaless JSON objects within a highly structured table. This allows you to have the consistency of a relational structure (users, transactions) while retaining the flexibility of a document store for secondary data (user settings, logging metadata).
   • Here’s the thing: JSONB often makes Mongo redundant for hybrid applications.

My painful lesson: My first attempt at a custom reporting dashboard using self-hosted Postgres cost me three full weekends just configuring replica sets and writing custom backup scripts. This is vital infrastructure, but it’s time taken away from feature development. Time is our most precious, non-renewable resource.

B. MongoDB: The Allure and the Trap

Mongo’s primary benefit is agility. Want to add a field to 1,000 documents without running a migration? Go for it. You just change the application code.

This speed is perfect for:

• Prototypes and MVPs where validation is the only goal.
• Data naturally organized as a document (e.g., a complex document editor where the entire document structure is one entity).

The Trap: When you inevitably need to join data across different collections (e.g., linking a "User" document to a "Comment" document, which then links to a "Post" document), you are forced to handle the complexity in your application layer. This usually involves multiple round-trip queries and messy indexing logic.

When the application grows, enforcing data integrity becomes a self-imposed nightmare. I once spent 48 hours debugging a weird bug caused by a missing reference ID that MongoDB happily accepted, but my application assumed was present.

The old advice was "use MongoDB when you need scale." Frankly, modern sharded Postgres setups, coupled with tools like Vitess, scale just as well, if not better, for transactional workloads. The scale argument for Mongo is mostly a historical footnote for indies.

C. Supabase: The BaaS Game-Changer

Supabase is what happens when you combine the power of Postgres with modern web sensibilities. It’s a complete backend service designed to remove friction.

The moment you define your tables in the Supabase dashboard:

1. Instant API: You immediately get a RESTful API and a client SDK that handles fetching, filtering, and mutation. No writing Node.js/Express boilerplate just to handle CRUD routes.

   • Code Snippet: JavaScript/Supabase client call

   // Fetch all active tasks for the current user in 2 lines, no backend needed
   const { data: tasks, error } = await supabase
     .from('tasks')
     .select('*')
     .eq('is_complete', false)
   

2. Row Level Security (RLS): This is a force multiplier. You write SQL policies directly on the database to define exactly who can read or write which rows. This is enterprise-grade security that allows you to safely expose your database directly to the client (via the proxy). It means I don't have to worry about my custom API endpoint accidentally leaking user data.

3. Authentication Baked In: User management, social logins, and token refreshing are handled out-of-the-box, tightly integrated with RLS.

My Personal Rube Goldberg Machine Analogy: Before BaaS, my typical MVP required Vercel/Next.js (frontend), a custom Node.js server (backend API), managed Postgres (database), and Auth0 (authentication). It worked, but keeping all those pieces humming felt like operating a delicate Rube Goldberg machine. Supabase collapses 70% of that setup into one well-integrated dashboard.

The 2026 Indie Decision Matrix

Choosing the database should depend on your app's DNA. Here is my pragmatic decision matrix for indie apps launching today:

Table: Indie Database Comparison Matrix (as above)

When I Choose...

1. I choose Supabase (BaaS) when:

   • I need to launch in under a month.
   • My app relies heavily on user accounts, real-time updates (like notifications or collaborative editing), and standard relational data (users, projects, tasks).
   • I want the reliability of Postgres but refuse to spend a second on writing boilerplate REST APIs.

2. I choose MongoDB when:

   • I am building a system where the data structure is inherently unknown or constantly changing, or where I genuinely don't need transactional integrity across entities. For example, a temporary user session tracker or a fire-and-forget logging utility.

3. I choose Self-Managed PostgreSQL when:

   • I have an extreme performance requirement that requires highly custom query tuning and direct access to the metal (or close to it).
   • I am absolutely allergic to any level of platform vendor lock-in, even if it costs me development time.

The Future is Integrated: Stop Writing Boilerplate

Let's be clear about the direction we are moving: The friction of managing infrastructure is rapidly decreasing. For the solo indie developer, our focus must shift away from writing repetitive API CRUD endpoints and toward solving genuine user problems.

In 2026, the cost of DevOps time far outweighs the marginal performance difference between Postgres and Mongo for 99% of apps.

If you are starting a new project today, seriously consider leveraging the existing scaffolding. Supabase provides that "standing on the shoulders of giants" feeling—you get a production-ready authentication and database infrastructure instantly, allowing you to focus on the unique 5% of your application logic that actually delivers value.

I’m currently building a new micro-SaaS utility, and the decision took me 30 seconds: Supabase. My data model is relational (accounts, workspaces, templates), and the sheer speed of having instant APIs for my Next.js frontend is a game-changer. That time saved is time I can spend on marketing, UI refinement, or frankly, just getting a decent night’s sleep.

What’s Your Data Modeling Philosophy?

The biggest mistake developers make is trying to force-fit a data model into the database they like, rather than the one the data requires.

If you pick Postgres (or Supabase), you are choosing a model where the relationships are paramount. If you choose Mongo, you are choosing a model where the individual document is king.

If you’re ready to dive in, my advice is to commit to a type-safe environment from the start. Tools like Zod and TypeScript, integrated with your database solution (especially when using tools that generate types from your schema, like Supabase's generated TypeScript definitions), will save you from the schema debt that often sinks faster, more flexible systems.

What’s your current database setup for your indie projects? Are you still living dangerously with MongoDB or have you been converted to the relational side? Drop your thoughts, favorite tools, or war stories on social media! Let’s keep the conversation going.