PostgreSQL vs MongoDB for Solo Developers

Quick Comparison

PostgreSQL Overview

PostgreSQL is the Swiss Army knife of databases. Relational tables, JSONB documents, full-text search, geospatial data, arrays, and custom types. It's a relational database that can also be your document store, your search engine, and your analytics platform. All in one process.

I run Postgres for every production application. The JSONB support means when I need flexible data alongside structured tables, I don't reach for a second database. User preferences, feature flags, API response caches. All stored in JSONB columns, fully indexed, queryable with SQL. That's one database to manage instead of two.

The managed hosting landscape is excellent. Supabase gives you free Postgres with a REST API. Neon offers serverless Postgres that scales to zero. Railway includes one-click Postgres. The days of Postgres being hard to set up are long gone.

MongoDB Overview

MongoDB stores data as JSON-like documents. No rigid schema, no ALTER TABLE commands, no migration headaches. You insert a document, and the database stores it. If the next document has different fields, that's fine too. The schema flexibility lets you iterate on your data model without downtime.

MongoDB Atlas makes getting started trivially easy. Create a free cluster in under a minute. The free tier includes 512MB of storage with shared RAM, which handles side projects and early-stage products comfortably. The Atlas UI lets you browse, query, and manage your data without touching the command line.

The aggregation pipeline is MongoDB's power feature. While it's not as readable as SQL for complex queries, it handles data transformations, grouping, and analysis within the database itself. For simple CRUD operations, the query syntax is intuitive and feels natural in JavaScript codebases.

Key Differences

Data modeling philosophy. PostgreSQL expects you to define your schema upfront. Tables, columns, types, constraints. This discipline catches bugs early. MongoDB lets you store whatever you want. This flexibility speeds up early development but can create data consistency problems as your application grows. I've seen MongoDB projects where the same "field" has three different types across documents.

JSONB vs documents. Here's the thing most MongoDB advocates miss: PostgreSQL's JSONB gives you document storage with all the benefits of a relational database underneath. You can have structured tables for your core data and JSONB columns for flexible data. MongoDB gives you only documents. You can't join collections efficiently, and you'll duplicate data to avoid slow lookups.

Querying power. SQL is the most powerful query language ever created. Joins, subqueries, window functions, CTEs, aggregations. PostgreSQL supports all of it. MongoDB's query language handles simple lookups well but becomes convoluted for complex queries. The aggregation pipeline works, but it's verbose and hard to debug.

Transactions. PostgreSQL has had rock-solid ACID transactions forever. MongoDB added multi-document transactions in version 4.0, but they come with performance caveats and limitations. If data consistency matters to your application, PostgreSQL is the safer choice.

Scaling. MongoDB's sharding is genuinely easier to set up for horizontal scaling. PostgreSQL scales vertically first and needs tools like Citus for horizontal scaling. For solo developers, this rarely matters. A single PostgreSQL instance handles millions of rows without breaking a sweat. Sharding is a problem for companies with millions of users, not solo developers.

Hosting costs. PostgreSQL is completely free to self-host or use through providers like Supabase and Neon. MongoDB Atlas free tier works for small projects, but costs escalate quickly. A dedicated MongoDB Atlas instance starts at $57/month. Comparable Postgres hosting is often cheaper.

When to Choose PostgreSQL

• You need relational data with joins and complex queries
• You want one database for structured data, JSON documents, and full-text search
• You value strict data integrity and ACID transactions
• Your framework has strong Postgres support (Django, Rails, most ORMs)
• You want the widest choice of free and managed hosting options

When to Choose MongoDB

• Your data is genuinely document-shaped with deeply nested structures
• You need a schema-less approach for rapid prototyping
• Your team is JavaScript-first and prefers JSON-native querying
• You're building a content management system with varied content types
• You need horizontal sharding at very large scale

The Verdict

PostgreSQL is the better choice for solo developers in nearly every scenario. The 9/10 vs 7/10 rating reflects a real-world truth: most applications have relational data. Users have orders. Orders have items. Items belong to categories. That's relational. And PostgreSQL handles relational data better than MongoDB while also handling document data through JSONB.

MongoDB is fine for specific use cases, particularly content management systems with highly variable schemas or applications where the data is genuinely document-shaped. But for the typical solo developer building a SaaS, marketplace, or web application, PostgreSQL does everything MongoDB does (through JSONB) plus everything MongoDB can't (through SQL).

Pick Postgres. Use JSONB columns when you need flexibility. Enjoy having one database that handles everything. Your future self will thank you when you need to write a complex query that would require three aggregation pipeline stages in MongoDB but takes five lines of SQL in Postgres.