/ tool-comparisons / Convex vs MongoDB for Solo Developers
tool-comparisons 5 min read

Convex vs MongoDB for Solo Developers

Comparing Convex and MongoDB for solo developers.

Quick Comparison

Feature Convex MongoDB
Type Reactive backend platform (database + functions + realtime) Document database (self-hosted or Atlas cloud)
Pricing Free tier (generous), then $25/mo (Pro) Atlas free tier (512 MB), then pay-as-you-go
Learning Curve Moderate (new paradigm, Convex way) Easy-Moderate (flexible documents, MQL)
Best For Realtime apps with automatic reactivity General-purpose document storage at any scale
Solo Dev Rating 8/10 7/10

Convex Overview

Convex is a reactive backend platform that combines a document database, server functions, and realtime subscriptions into one cohesive system. You write your backend logic as Convex functions (queries, mutations, and actions), and the platform handles reactivity automatically. When data changes, every client subscribed to a query that depends on that data gets updated instantly.

For solo developers, Convex removes a huge amount of plumbing. You do not set up a database, write API routes, configure WebSockets, or manage cache invalidation. You define your schema, write functions, and the frontend stays in sync automatically.

The development experience is TypeScript-first. Your schema generates types that flow through your queries and mutations all the way to your React hooks. If a field name changes, your IDE tells you everywhere it breaks before you even run the code.

The free tier includes 1 million function calls, 1 GB storage, and 16 million database operations per month. That is enough to build and launch a real product without paying anything.

MongoDB Overview

MongoDB is the most popular document database. You store data as JSON-like documents in collections, with no fixed schema required. This flexibility made MongoDB the go-to choice for prototyping and applications where the data model evolves rapidly.

MongoDB Atlas (the managed cloud version) has a free tier with 512 MB of storage. The managed service handles backups, scaling, and security. For solo developers who do not want to manage database infrastructure, Atlas is the standard choice.

The query language (MQL) is powerful but different from SQL. You chain operators and use aggregation pipelines for complex queries. The learning curve is manageable, but developers coming from SQL often find MongoDB's approach unfamiliar at first.

MongoDB's ecosystem is massive. Mongoose for Node.js, Motor for Python, official drivers for every major language, and a large community producing tutorials, courses, and Stack Overflow answers.

Head-to-Head Comparison

Criteria Convex MongoDB
Data Model Documents with schema validation Flexible documents (optional schema)
Realtime Built-in (automatic reactive queries) Change Streams (manual setup)
Backend Functions Included (queries, mutations, actions) None (bring your own API)
Type Safety Full (schema to frontend) Partial (Mongoose schemas, or manual)
Free Tier 1M function calls, 1 GB storage 512 MB storage (Atlas)
Self-Hosting No Yes (open source Community Edition)
Vendor Lock-in High (Convex-specific API) Low-Moderate (standard MongoDB API)
Aggregations JavaScript functions Aggregation Pipeline (powerful)
Ecosystem Size Small (growing) Massive (largest NoSQL ecosystem)
Auth Built-in (Clerk/Auth0 integration) None (bring your own)

When to Pick Convex

Pick Convex when you are building a realtime application and you want reactivity without the work. Collaborative tools, live dashboards, chat applications, multiplayer features: anything where multiple users need to see the same data update simultaneously is where Convex shines.

It is the right choice when you want to skip building a backend entirely. Convex functions replace your API layer. You write a query function, call it from React, and it stays reactive. No Express server, no REST endpoints, no GraphQL schema, no WebSocket setup.

Choose Convex if you are a React developer who wants the fastest path from idea to working product. The integration with React (and Next.js) is excellent. The development loop of writing a function and immediately using it in your component is hard to beat for speed.

When to Pick MongoDB

Pick MongoDB when you need a general-purpose document database with maximum flexibility. MongoDB works with any backend framework, any language, and any deployment model. You are not locked into a specific way of building your application.

It is the right choice when your data model is genuinely unstructured or semi-structured. Logs, user-generated content with variable fields, IoT sensor data: these use cases benefit from MongoDB's schema flexibility.

Choose MongoDB when ecosystem and community matter. MongoDB has been around since 2009. Every question you might have has been answered on Stack Overflow. Every language has mature drivers. Finding developers who know MongoDB is easy. For a solo developer, this means fewer dead ends when you get stuck.

MongoDB also makes sense when you might need to self-host. The Community Edition is open source and runs on any server. If you want full control over your data and infrastructure, MongoDB gives you that option while Atlas provides the managed alternative.

The Verdict

Convex and MongoDB represent two different philosophies. MongoDB is a database. Convex is a backend platform that includes a database.

For solo developers building React applications that need realtime features, Convex is the faster path. You skip weeks of backend plumbing and focus on your product. The developer experience is polished, the free tier is generous, and the automatic reactivity is genuinely impressive.

For solo developers who want maximum flexibility, proven technology, and a massive ecosystem, MongoDB is the safer long-term bet. You control every layer of your stack. You can swap frameworks, languages, and deployment platforms without changing your database.

If your application is primarily a React web app with realtime requirements, try Convex first. If you are building something that spans multiple platforms, needs complex aggregations, or might outlive any single framework, go with MongoDB.