MySQL vs MongoDB for Solo Developers

Quick Comparison

MySQL Overview

MySQL is the most widely deployed open-source relational database in the world. It powers the LAMP stack, WordPress, and countless web applications. You store data in tables with defined columns, enforce relationships with foreign keys, and query everything with SQL. It is straightforward, proven, and supported by every hosting provider in existence.

For a solo developer, MySQL's strength is its simplicity and ubiquity. Setting up a MySQL database takes minutes. The documentation is extensive, the community is huge, and when you run into problems, someone has already solved them on Stack Overflow. Frameworks like Laravel, Rails, and Django all support MySQL out of the box.

MongoDB Overview

MongoDB stores data as flexible JSON-like documents in collections instead of rows in tables. There is no fixed schema. A document in the same collection can have different fields from its neighbors. This flexibility is MongoDB's core appeal, especially during the early stages when your data model is still evolving.

MongoDB Atlas provides a genuinely useful free tier (M0) with 512 MB of storage, a shared 3-node cluster, up to 500 connections, and roughly 100 operations per second. The Atlas interface is clean, and features like full-text search (Atlas Search), charts, and triggers are built in. For prototyping and early-stage development, MongoDB makes it easy to get started.

The aggregation pipeline replaces SQL joins and provides powerful data transformation, but it has a steep learning curve. Once you understand stages like $lookup, $unwind, and $group, you can do complex data processing, though it never feels as intuitive as SQL.

Key Differences

Schema flexibility is the headline difference. MySQL requires you to define your table structure before inserting data. Adding a column means running ALTER TABLE. MongoDB lets you store any document structure and change it freely. For a solo developer exploring an idea, this flexibility speeds up early development. But it also means your application code must handle documents that might be missing fields or have inconsistent types.

Joins and relationships favor MySQL. Relational data, things like users who have orders that contain products, is MySQL's strength. You define foreign keys, write JOIN queries, and the database enforces referential integrity. MongoDB has $lookup for joining collections, but it is slower, more complex, and does not enforce referential integrity. If your data is naturally relational, MySQL (or Postgres) is the better fit.

MongoDB is easier to start, harder to scale correctly. Throwing JSON documents into a collection is fast. But as your data grows, you need to think about indexes, schema validation, and data consistency. Without planning, MongoDB databases become a mess of inconsistent documents that are hard to query efficiently.

SQL skills are more transferable. MySQL, PostgreSQL, SQLite, PlanetScale, CockroachDB, Supabase, Neon. They all use SQL. Learning MySQL teaches you skills that work across the entire relational database ecosystem. MongoDB's query language and aggregation pipeline are unique to MongoDB.

Cost at scale diverges. MySQL is free and runs on any cheap VPS. MongoDB Atlas free tier is great for starting, but dedicated clusters start at $57/mo. Self-hosted MongoDB is free but requires more operational knowledge than self-hosted MySQL.

Data consistency is MySQL's advantage. MySQL enforces types, constraints, and foreign keys by default. If you try to insert a string into an integer column, it fails. MongoDB accepts whatever you send. For a solo developer without a QA team, having the database catch type errors and constraint violations is valuable.

By the Numbers (2026)

Both projects are mature, actively maintained, and used at enormous scale. Here is where each stands as of late May 2026.

Versions and release cadence. MySQL shipped its 9.7 LTS release in April 2026, the first major LTS line since 8.4, with the 8.4 LTS series still receiving patches up to 8.4.9. An LTS series carries five years of premier support plus three more of extended support, so MySQL 9.7 is supported into 2034. MongoDB Server's latest stable release is 8.3.1 from May 4, 2026, while the 8.0 line is the current long-term-support GA series with security support through October 31, 2029. GA major releases of MongoDB Server are supported for 30 months.

Adoption signals. The mysql/mysql-server mirror sits at roughly 12.3k GitHub stars, while mongodb/mongo carries about 28.3k. The Node drivers tell a closer story. The mysql2 package pulled about 10.7 million npm downloads in the week of May 21 to 27, 2026, and the official mongodb driver pulled about 11.3 million in the same window. Both are firmly in the top tier of database packages.

MySQL pricing. MySQL Community Edition is released under the GPLv2 and is free to download, run, and self-host. The paid path is MySQL Enterprise Edition, sold by Oracle on a per-server subscription, but a solo developer almost never needs it. The practical cost of running MySQL is the cost of the box it sits on.

MongoDB Atlas limits and pricing. The free Atlas M0 cluster gives you 512 MB of storage on a fixed 3-node replica set, a cap of 500 concurrent connections, roughly 100 operations per second, a 10 GB in / 10 GB out data-transfer allowance over any rolling 7-day window, and no managed backups (you fall back to mongodump and mongorestore). M0 clusters auto-pause after 30 days with zero connections. The next step up, the Flex tier, runs $0.011 per hour and is capped at $30 per month for 5 GB of storage. The first dedicated tier, M10, starts at $0.08 per hour, which works out to about $56.94 per month, and gives you 2 GB of RAM, 2 vCPUs, and 10 to 128 GB of storage.

Real Cost at Solo-Dev Scale

Say you are running one small production web app. Assume a single database node, a few gigabytes of data, modest traffic, and that you, the solo developer, are the only operator. Here is what each option actually costs per month, using real published rates.

Self-host both on the same cheap box (cheapest path). A DigitalOcean basic Droplet with 1 GB of RAM is $6 per month, and the 512 MB Droplet is $4 per month. MySQL Community Edition is free under the GPLv2, and MongoDB Community Edition is free to self-host as well. So the floor for either database is the same: the price of the Droplet, around $4 to $6 per month, plus your own time for patching, backups, and monitoring. At this tier MySQL and MongoDB cost identically. The difference is operational effort, and self-hosted MySQL is the more widely documented thing to keep alive.

Managed, hands-off path. This is where the two diverge. DigitalOcean's managed MySQL starts at $15 per month for a single 1 GB node, with a highly available pair starting at $30 per month. MongoDB Atlas has no equivalent in the $15 range. You go from the free M0 (which is a sandbox, not a production tier given the 100 ops/sec ceiling and lack of backups) and the $30/month Flex cap straight to the dedicated M10 at about $57 per month. So for a managed, backed-up, production-grade single node:

• Managed MySQL: about $15 per month
• MongoDB Atlas dedicated M10: about $57 per month

That is roughly a 3.8x difference for the entry-level managed production tier, before any data-transfer or backup add-ons. The gap exists because Atlas's cheap tiers are explicitly sandboxes, while a $15 managed MySQL node is a real, if small, production database.

Assumptions, stated plainly: one node, no high-availability replica, a few GB of data, traffic that fits inside an entry-level instance, and prices as published on the linked pages on May 29, 2026. Scale up and both bills climb; the relative shape (self-hosting equal, managed MySQL cheaper at the entry tier) holds at the bottom where most solo projects live.

When to Choose MySQL

• Your data is naturally relational (users, orders, products, categories)
• You want the database to enforce data integrity and types
• You are building with PHP/Laravel or WordPress
• You value SQL skills that transfer to other databases
• You want the cheapest possible hosting (every provider supports MySQL)

When to Choose MongoDB

• Your data model is genuinely document-oriented (CMS content, logs, IoT data)
• Your schema is changing rapidly during early development
• You need full-text search built into your database (Atlas Search)
• You want a free managed database tier for prototyping
• Your data does not have complex relational dependencies

The Verdict

Both score 7/10 for solo developers, and the right choice depends on your data. If your data has relationships (users own things, things belong to categories, transactions reference accounts), MySQL is the better fit. Relational databases exist because relational data is the most common type of data in web applications.

If your data is genuinely document-oriented, where each record is a self-contained blob that rarely references other records, MongoDB works well. Think content management systems, event logs, or configuration stores.

My honest take: most solo developers building web applications should reach for a relational database. And if you are choosing a relational database, PostgreSQL beats MySQL on features. But between MySQL and MongoDB specifically, pick whichever matches your data structure. Do not force relational data into documents, and do not force document data into tables.

Sources

All figures below were checked on May 29, 2026.

• MySQL versions and LTS support timeline: endoflife.date/mysql
• MongoDB Server versions and LTS / GA support window: endoflife.date/mongodb
• MySQL GitHub stars (mysql/mysql-server): github.com/mysql/mysql-server
• MongoDB GitHub stars (mongodb/mongo): github.com/mongodb/mongo
• mysql2 npm weekly downloads: api.npmjs.org/downloads/point/last-week/mysql2
• mongodb npm weekly downloads: api.npmjs.org/downloads/point/last-week/mongodb
• mysql2 latest version: registry.npmjs.org/mysql2/latest
• mongodb driver latest version: registry.npmjs.org/mongodb/latest
• MongoDB Atlas tier pricing (M0, Flex, M10): mongodb.com/pricing
• MongoDB Atlas free cluster (M0) limits: mongodb.com/docs/atlas/reference/free-shared-limitations
• DigitalOcean Droplet pricing: digitalocean.com/pricing/droplets
• DigitalOcean managed MySQL pricing: digitalocean.com/pricing/managed-databases