PostgreSQL vs MongoDB for Solo Developers

Quick Comparison

All version, pricing, star, and download figures above are sourced and dated in the Sources section (checked 2026-05-29). The postgres/postgres repository is the read-only Git mirror, so its star count understates real adoption; treat it as a directional signal, not a popularity verdict.

By the Numbers (2026)

Here is the verifiable state of both projects as of 2026-05-29. Every figure links to its source at the end of this post.

Versions. PostgreSQL's latest stable release is 18.4, shipped 2026-05-14 as part of a coordinated update across the 14 through 18 branches that fixed 11 security issues and over 60 bugs. MongoDB's current stable server release is the 8.3 series.

Licensing. PostgreSQL ships under the permissive PostgreSQL License, which is close to MIT or BSD and lets you do almost anything. MongoDB Community Server ships under the Server Side Public License (SSPL), which MongoDB adopted in 2018. The SSPL is the reason MongoDB is not classified as open source by the Open Source Initiative, and it is why managed MongoDB offerings outside Atlas became rare. For a solo developer this mostly does not matter, but it matters if you ever want to resell a hosted version of your stack.

Adoption signal from npm. In the week of 2026-05-21 through 2026-05-27, the Node Postgres driver pg saw 29,260,035 weekly downloads. On the MongoDB side, the official mongodb driver saw 11,312,820 and the popular mongoose ODM saw 5,158,898. Even adding the two MongoDB packages together (16.5M) leaves Postgres ahead by a wide margin in the JavaScript ecosystem, which is notable given MongoDB's reputation as the JavaScript-native database. Latest published versions at check time were pg 8.21.0, mongodb 7.2.0, and mongoose 9.6.3.

GitHub stars. The mongodb/mongo repository has 28,334 stars against postgres/postgres at 21,021. Read that gap with care, because postgres/postgres is the read-only Git mirror of a project that has lived on its own mailing-list and CVS/Git infrastructure for decades, so its star count badly undercounts real interest. MongoDB develops in the open on GitHub, so its stars are a truer reflection of GitHub-native attention. Stars measure GitHub visibility, not production usage, and the npm numbers above are the better adoption proxy for solo developers.

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, which reached general availability in 2018 (more than two decades after Postgres shipped its row-level MVCC model). The current MongoDB server release is 8.3, so the feature is mature now, but it still carries documented performance caveats and limits around transaction duration. 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. Supabase Free gives you a 500 MB database, and Neon Free gives you 0.5 GB per project with compute that scales to zero after five minutes of inactivity. MongoDB Atlas free tier (M0) works for small projects with 512 MB of storage on shared RAM, but the jump to a dedicated instance is steep. The cheapest dedicated Atlas tier (M10) starts at $56.94 per month for 2 GB of RAM and 2 vCPUs. The comparable step up on the Postgres side is Supabase Pro at $25 per month with an 8 GB included disk, so dedicated Postgres hosting is roughly half the price of dedicated Atlas at the entry point.

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.

Real Cost at Solo-Dev Scale

Both databases are free to self-host, so the cost decision only appears once you move to managed hosting. Let me model a realistic solo-dev workload and compute the actual monthly bill from each vendor's published rates.

Assumptions. A small SaaS that has outgrown the free tier. Roughly 8 GB of stored data, one always-on production database, and a workload modest enough that a 2 GB RAM instance is plenty. This is the stage where most side projects start charging real customers.

MongoDB Atlas path. The free M0 tier caps at 512 MB, so 8 GB of data forces you off it. The Flex tier covers up to 5 GB and bills usage-based between $8 and $30 per month, so 8 GB pushes you past it too. That lands you on the cheapest dedicated tier, M10, at a floor of $56.94 per month for 2 GB of RAM, 2 vCPUs, and 10 to 128 GB of storage. Call it about $57 per month before any add-ons.

Supabase path. The free tier caps at 500 MB, so 8 GB forces the upgrade. Supabase Pro is $25 per month and includes an 8 GB disk, then $0.125 per additional GB. At exactly 8 GB you pay the flat $25 with no overage. That is your full bill.

Neon path. Neon's free tier caps at 0.5 GB per project. The Launch plan is pay-as-you-go with no monthly minimum, billing $0.35 per GB-month of storage plus $0.106 per CU-hour of compute. Storage for 8 GB is 8 times $0.35, which is $2.80 per month. Compute is the variable part because Neon scales to zero when idle. A low-traffic SaaS that is genuinely active only a few hours a day will land in the low tens of dollars of compute. As a rough planning number, budget $15 to $30 per month all-in at this scale, with the real figure depending on how often your database is actually awake.

The math at 8 GB.

The Postgres-managed options come in at roughly half the cost of dedicated Atlas for the same data footprint, and Neon's scale-to-zero model can go lower still for an app that is idle most of the day. The gap exists because Atlas has no cheap always-on dedicated rung between its usage-capped Flex tier and the $57 M10. If predictable spend matters and you are past the free tier, Supabase Pro is the simplest number to reason about. Rerun this with your own storage and traffic, because compute-billed plans like Neon move with usage. Check current pricing before committing, since all three vendors revise rates.

Sources

• PostgreSQL latest version (18.4, released 2026-05-14): https://www.postgresql.org/ (checked 2026-05-29)
• MongoDB current stable server release (8.3): https://www.mongodb.com/docs/manual/release-notes/ (checked 2026-05-29)
• MongoDB Atlas pricing (M0 512 MB, Flex $8 to $30, M10 $56.94/mo, 2 GB RAM, 2 vCPU): https://www.mongodb.com/pricing (checked 2026-05-29)
• Supabase pricing (Free 500 MB, Pro $25/mo with 8 GB disk): https://supabase.com/pricing (checked 2026-05-29)
• Neon pricing (Free 0.5 GB/project scales to zero, Launch $0.106/CU-hour + $0.35/GB-month): https://neon.com/pricing (checked 2026-05-29)
• MongoDB multi-document ACID transactions in 4.0 (2018): https://www.mongodb.com/company/blog/product-release-announcements/mongodb-multi-document-acid-transactions-general-availability (checked 2026-05-29)
• pg npm latest version 8.21.0: https://registry.npmjs.org/pg/latest (checked 2026-05-29)
• mongodb npm latest version 7.2.0: https://registry.npmjs.org/mongodb/latest (checked 2026-05-29)
• mongoose npm latest version 9.6.3: https://registry.npmjs.org/mongoose/latest (checked 2026-05-29)
• pg weekly downloads 29,260,035 (2026-05-21 to 2026-05-27): https://api.npmjs.org/downloads/point/last-week/pg (checked 2026-05-29)
• mongodb weekly downloads 11,312,820 (2026-05-21 to 2026-05-27): https://api.npmjs.org/downloads/point/last-week/mongodb (checked 2026-05-29)
• mongoose weekly downloads 5,158,898 (2026-05-21 to 2026-05-27): https://api.npmjs.org/downloads/point/last-week/mongoose (checked 2026-05-29)
• GitHub stars postgres/postgres (21,021): https://github.com/postgres/postgres (queried via authenticated GitHub API, checked 2026-05-29)
• GitHub stars mongodb/mongo (28,334): https://github.com/mongodb/mongo (queried via authenticated GitHub API, checked 2026-05-29)