MongoDB vs Redis for Solo Developers

Comparing MongoDB and Redis for solo developers. Features, pricing, pros and cons, and which one to pick for your next project.

Quick Comparison

Feature	MongoDB	Redis
Type	Document-oriented NoSQL database	In-memory data store and cache
Latest server version	8.2 (GA September 16, 2025), point release 8.2.9	8.8.0 (released May 25, 2026)
Managed free tier	Atlas M0, 512 MB storage, 500 connections, 100 ops/sec	Redis Cloud, 30 MB, 30 connections, 100 ops/sec
Entry paid tier	Atlas Flex from $0.011/hr (about $8/mo)	Redis Cloud Essentials from $0.007/hr ($5/mo minimum)
Production dedicated	Atlas M10 at $0.08/hr (about $56.94/mo)	Essentials spec tiers up to 12 GB, then Pro
GitHub stars (server repo)	28,334	74,579
npm weekly downloads (driver)	mongodb 11.3M	ioredis 18.4M, node-redis 9.8M
Learning Curve	Easy	Easy
Best For	Apps with flexible schemas, document-based data	Caching, sessions, queues, real-time features
Solo Dev Rating	7/10	8/10

By the Numbers (2026)

Here is where the two projects stand on the day this comparison was checked, May 29, 2026. Every figure below comes from an official registry, API, or vendor page, and each is cited at the end.

Latest versions. MongoDB 8.2 reached general availability on September 16, 2025, and it was the first minor release offered for Community Edition and Enterprise Server alongside Atlas. The current point release on the server repo is 8.2.9. Redis shipped server version 8.8.0 on May 25, 2026, so Redis cuts releases on a noticeably faster cadence than the MongoDB server.

Driver versions. The official MongoDB Node driver (mongodb) is at version 7.2.0. On the Redis side, ioredis is at 5.11.0 and the official redis client (node-redis) is at 6.0.0.

Adoption on npm (week of May 21 to May 27, 2026). The mongodb driver pulled 11,312,820 weekly downloads. For Redis, ioredis pulled 18,361,400 and the official redis client pulled 9,790,245. Combine the two Redis clients and Redis client installs outnumber MongoDB driver installs by a wide margin, which tracks with Redis being a near-universal add-on rather than a primary-database choice.

GitHub stars. The Redis server repo sits at 74,579 stars against 28,334 for the MongoDB server repo, more than double. On the client side, the MongoDB Node driver has 10,182 stars, node-redis has 17,531, and ioredis has 15,284.

Managed free tiers. MongoDB Atlas M0 gives you 512 MB of storage, up to 500 connections, 100 operations per second, and 10 GB in plus 10 GB out of data transfer over a rolling 7-day window. It pauses after 30 days of zero connections. Redis Cloud's free tier gives you a 30 MB dataset, 30 concurrent connections, 100 ops/sec, and 5 GB of monthly bandwidth. The headline difference is storage, MongoDB's 512 MB versus Redis's 30 MB, which makes sense because Redis is holding everything in RAM and RAM is the expensive resource.

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

Real Cost at Solo-Dev Scale

Pricing arguments only mean something with a concrete workload attached, so here is one. Picture a small SaaS side project that has outgrown the free tiers but is nowhere near needing dedicated hardware. Say it stores a few gigabytes of persistent application data and uses a small cache layer for sessions and rate limiting. I am using real, currently published per-unit rates here, and you should still check the live pricing pages before you commit because cloud rates move.

The MongoDB side of the bill. Once you pass the 512 MB M0 free tier, the next stop is Atlas Flex. Flex bills at $0.011 per hour at the lowest throughput band (0 to 100 ops/sec) and scales up by operations per second, topping out at roughly $30 per month with 5 GB of storage. At the entry band that is about $8 per month. If the project's writes are bursty and stay under a couple hundred ops/sec, expect to land between the $8 floor and roughly $21 per month (the 200 to 300 ops/sec band). Cross into steady production traffic or need more than 5 GB and you jump to a dedicated M10, which is $0.08 per hour, about $56.94 per month, for 2 GB of RAM, 2 vCPUs, and 10 to 128 GB of storage.

The Redis side of the bill. Redis Cloud's free tier caps at 30 MB, which is fine for a tiny session store but runs out fast. The first paid step is Essentials, which starts at $0.007 per hour with a $5 per month minimum. A small cache and session store comfortably fits the lower Essentials tiers (250 MB or 1 GB of dataset), so budget something in the $5 to roughly $20 per month range depending on the dataset size you pick.

Putting it together. A realistic combined monthly bill for this side project, persistent data on Atlas Flex plus a small Redis Cloud cache, lands somewhere around $13 to $40 per month at the rates above ($8 to $30 for Flex plus $5 to a low-double-digit figure for Redis Essentials). That is the actual shape of the cost, and it confirms the point the rest of this post keeps making, you are usually paying for both because they do different jobs, not choosing one to avoid the other. The only scenario where you genuinely pick one is the free-tier prototype stage, and even there the two free tiers serve different needs (512 MB of durable documents versus 30 MB of in-memory speed).

Assumptions: a few GB of persistent data, a small cache and session workload under a few hundred ops/sec, single-region, no significant egress beyond the included transfer. Heavier traffic, larger datasets, backups, or multi-region all push these numbers up, so treat the figures as a floor.

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.