MongoDB vs Redis for Solo Developers

Quick Comparison

MongoDB Overview

MongoDB stores data as JSON-like documents in collections. No rigid schema, no predefined columns. You insert a document and the database stores it as-is. Need to add a new field? Just include it in the next document. No migration required. No downtime. The schema evolves with your application.

MongoDB Atlas makes getting started effortless. A free cluster with 512MB of storage handles side projects and early-stage products. The Atlas UI lets you browse collections, run queries, and manage indexes without CLI tools. For developers who want a visual database management experience, Atlas delivers.

The aggregation pipeline handles data transformations within the database. Grouping, filtering, joining (with $lookup), and reshaping documents all happen server-side. For analytics queries over document data, it's powerful. For simple CRUD operations, the query syntax feels natural in JavaScript codebases.

Redis Overview

Redis is the in-memory data store that powers the fast layer of modern web applications. Sub-millisecond response times for reads and writes. Strings, hashes, lists, sets, sorted sets, streams, and more. It's not just a key-value cache. It's a versatile data structure server.

I use Redis in every production application. Session storage, rate limiting, job queues, real-time leaderboards, pub/sub for WebSocket broadcasting. Redis handles all of these use cases with the same sub-millisecond latency. When your main database is the bottleneck, a Redis cache layer can improve response times by 10-100x.

Redis has evolved beyond caching. Redis Stack adds JSON document support, full-text search, time series data, and graph queries. You can use Redis as a lightweight primary database for specific use cases. But its real power remains as the speed layer that sits between your application and your primary database.

Key Differences

These databases solve different problems. MongoDB is a primary database for persistent data storage. Redis is primarily a cache, session store, and real-time data layer. Comparing them directly is like comparing a filing cabinet to a desk. You probably need both, not one or the other.

Persistence model. MongoDB writes data to disk. Your data survives restarts, crashes, and power failures. Redis stores data in memory. It has persistence options (RDB snapshots and AOF logs), but data loss during crashes is possible depending on configuration. For data you can't afford to lose, MongoDB (or any disk-based database) is the safer choice.

Data size constraints. MongoDB stores data on disk. Your dataset can be much larger than your server's RAM. Redis stores everything in memory. Your dataset is limited by available RAM, which is expensive. A $20/month server might give you 4GB of RAM but 80GB of disk. This fundamentally limits what you store in Redis.

Query capabilities. MongoDB supports rich queries: filtering, sorting, aggregation, text search, and geospatial queries. Redis queries are primarily key-based lookups. Redis Stack adds more query capabilities, but it's not designed for the complex filtering and aggregation that MongoDB handles. If you need to query your data in flexible ways, MongoDB is the better fit.

Speed. Redis is faster. Dramatically faster. Sub-millisecond operations versus MongoDB's single-digit millisecond operations (with indexes). For use cases where latency matters, like session lookups, rate limiting, or real-time leaderboards, Redis is the obvious choice.

Use case overlap. Redis Stack with JSON support can function as a document store similar to MongoDB. MongoDB with in-memory storage engine can function as a fast cache. But neither excels at the other's primary use case. Use each for what it's designed for.

When to Choose MongoDB

• You need a primary database for persistent document storage
• Your application data is document-shaped with nested structures
• You need rich querying, aggregation, and full-text search on your primary data
• Your dataset will grow larger than available server RAM
• You want a managed database with Atlas's visual management tools

When to Choose Redis

• You need sub-millisecond caching for your primary database queries
• You're implementing sessions, rate limiting, or job queues
• You need real-time features like pub/sub, leaderboards, or live counters
• You want a speed layer between your application and your primary database
• You need versatile data structures (sorted sets, streams, lists) for specific use cases

The Verdict

The honest answer is that most applications need both, not one or the other. MongoDB (or PostgreSQL, which I'd recommend over MongoDB) serves as your primary data store. Redis serves as your caching, session, and real-time layer.

If you're forced to pick one, MongoDB is the better primary database because it handles persistent storage, rich queries, and your full dataset. Redis can't serve as your only database for most applications because of RAM constraints and persistence limitations.

But if you already have a primary database and you're deciding whether to add MongoDB or Redis as a supplementary data store, Redis is almost always the right addition. Caching, sessions, and queues are universal needs, and Redis handles all of them at sub-millisecond speeds.

The 8/10 for Redis and 7/10 for MongoDB reflect their value to solo developers. Redis is nearly essential for any production application. MongoDB is one of several viable primary database options, and frankly, PostgreSQL with JSONB handles most MongoDB use cases better. Use Redis alongside your primary database. Use PostgreSQL instead of MongoDB. That's the solo developer playbook.