PlanetScale vs DynamoDB for Solo Developers

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

Quick Comparison

Feature	PlanetScale	DynamoDB
Type	Managed MySQL on Vitess (also offers managed Postgres)	Fully managed NoSQL (key-value and document)
Engine version	Vitess 23.0.0 (released 2025-11-04)	Managed AWS service, no public version; SDK `@aws-sdk/client-dynamodb` 3.1056.0
Cheapest entry	$39/mo (PS-10, 3-node HA MySQL); Postgres single node from $5/mo	$0/mo on the always-free 25GB tier; then pay-per-request
Free tier	None (Hobby tier retired)	Yes, 25GB storage always-free per Region
Pay-per-request rates	Flat plan plus storage and egress overage	$0.625 per million writes, $0.125 per million eventually-consistent reads, $0.25 per GB-month storage
Learning Curve	Easy if you know SQL	Hard, requires access-pattern-first modeling
Open-source core	Yes, Vitess (about 21K GitHub stars)	No, proprietary AWS API
Best For	MySQL apps needing zero-downtime schema changes	AWS-native apps needing key-value storage at scale
Solo Dev Rating	6/10	5/10

PlanetScale Overview

PlanetScale wraps MySQL in a modern developer experience. Built on Vitess (the technology that scaled YouTube's databases), it gives you database branching, non-blocking schema changes, and a workflow that treats database migrations like pull requests. You branch, test, merge. No more crossing your fingers during production ALTER TABLE statements.

The DX is genuinely good. The CLI works well, the web dashboard is clean, and everything feels designed for developers rather than database administrators. When I've needed MySQL for a project, PlanetScale's workflow made schema management much less stressful than raw MySQL administration.

The catch is pricing. With no free tier, you're starting at $39/mo. For a solo developer running multiple side projects, that cost adds up fast. And the foreign key limitation (disabled by default because Vitess doesn't handle them well) means you're giving up a fundamental SQL feature.

DynamoDB Overview

DynamoDB is AWS's fully managed NoSQL database. It delivers single-digit millisecond response times at any scale, and it truly means any scale. Netflix, Lyft, and Airbnb all run on DynamoDB. It handles millions of requests per second without breaking a sweat.

But scale is DynamoDB's pitch, and it comes with a brutal learning curve. Data modeling in DynamoDB is nothing like SQL. You design your tables around your access patterns, not your data relationships. Single-table design, partition keys, sort keys, GSIs, LSIs. It's an entirely different way of thinking about data.

I've built small projects on DynamoDB's free tier and it works, but the mental overhead is constant. Every new feature requires rethinking your access patterns. Every query needs an index planned in advance. For a solo developer who just wants to store and retrieve data, this is way too much friction.

Key Differences

SQL vs NoSQL is the fundamental divide. PlanetScale gives you MySQL with relational tables, joins, and structured queries. DynamoDB gives you key-value and document storage where you trade query flexibility for performance at scale. If your data is relational (users have orders, orders have items), PlanetScale is the natural fit. If it's key-value (session data, user profiles, event logs), DynamoDB can work.

Data modeling complexity is night and day. With PlanetScale, you design your schema, write SQL, and the ORM handles the rest. With DynamoDB, you must understand your query patterns before you write a single line of data. Adding a new query pattern later might require restructuring your entire table or adding a new Global Secondary Index. For solo developers iterating quickly, this is a serious constraint.

Pricing models differ completely. PlanetScale charges a flat $39/mo minimum. DynamoDB offers pay-per-request pricing where you pay for actual reads and writes, plus a 25GB free tier. For low-traffic projects, DynamoDB can be nearly free. For moderate traffic, it can get expensive quickly without provisioned capacity planning.

Vendor lock-in is real with DynamoDB. PlanetScale uses standard MySQL, so you can migrate to any MySQL host. DynamoDB's API is proprietary to AWS. Once you build on DynamoDB, moving off AWS means rewriting your entire data layer. PlanetScale gives you an exit path. DynamoDB does not.

Tooling and local development. PlanetScale works with any MySQL client, any ORM, any SQL tool you already know. DynamoDB requires the AWS SDK, DynamoDB Local for testing, and specialized knowledge. Your existing SQL skills don't transfer.

By the Numbers (2026)

Here is the verifiable state of both tools as of late May 2026.

PlanetScale

No free tier. The old Hobby plan was retired, so every database lands on a paid plan at creation. PlanetScale support confirms there is no free plan and no perpetual free tier.
The cheapest 3-node highly available MySQL cluster (Vitess) is the PS-10 at $39 per month, which provisions 1/8 vCPU and 1 GiB of memory. PlanetScale also sells managed Postgres, where a single-node PS-5 starts at $5 per month and a 3-node HA PS-5 starts at $15 per month.
PlanetScale Metal, the NVMe-backed tier with unlimited IOPS, starts at $50 per month (M-10 Postgres, which includes 10 GiB of storage).
The engine underneath is Vitess 23.0.0, released on 4 November 2025.
Vitess is open source. Its GitHub repository (vitessio/vitess) shows roughly 20,976 stars, 2,343 forks, and 966 open issues. This is the same engine that scaled YouTube.
The MySQL driver most PlanetScale Node apps use, mysql2, pulls about 10,660,594 npm downloads per week. PlanetScale's own serverless driver @planetscale/database pulls about 187,805 per week.

DynamoDB

There is a permanent free tier of 25 GB of storage per Region, with no expiration.
On-demand pricing in US East (N. Virginia) is $0.625 per million write request units, $0.125 per million eventually-consistent read request units (strongly-consistent reads cost double at $0.250 per million), and $0.25 per GB-month for standard-class storage. These rates reflect the roughly 50 percent on-demand price cut AWS made in November 2024.
A write request unit covers an item up to 1 KB. A read request unit covers an eventually-consistent read of an item up to 4 KB. Larger items consume more units, which is the detail that quietly inflates real bills.
There is no public version number for the managed service. The client side is the AWS SDK; @aws-sdk/client-dynamodb is at version 3.1056.0 and pulls about 7,094,587 npm downloads per week.

Real Cost at Solo-Dev Scale

Pricing models this different are hard to compare in the abstract, so here is a concrete workload. Assume a small SaaS side project doing 5 million reads and 1 million writes per month, storing 5 GB of data, with reads served as eventually-consistent (the DynamoDB default and the cheaper option).

Assumptions

5,000,000 reads per month, each on an item under 4 KB, so 1 read request unit each.
1,000,000 writes per month, each on an item under 1 KB, so 1 write request unit each.
5 GB stored, which sits inside DynamoDB's 25 GB free storage allowance.
No Global Secondary Indexes (each GSI write is billed again, so adding them changes the math).

DynamoDB on-demand

Reads: 5 million times $0.125 per million equals $0.63.
Writes: 1 million times $0.625 per million equals $0.63.
Storage: 5 GB is under the 25 GB free tier, so $0.00.
Monthly total: about $1.26, plus any data transfer out.

PlanetScale

The smallest production MySQL cluster is the PS-10 at a flat $39 per month, regardless of whether you serve 6 million requests or 60 million, until you exceed the included resources and pay overage.
Monthly total: $39 at this workload.

At this scale DynamoDB wins on price by a wide margin, roughly $1 versus $39, because pay-per-request rewards low, spiky traffic and the storage fits the free tier. The picture flips as you scale. Run the same item sizes at 200 million reads and 50 million writes per month and DynamoDB lands around 200 times $0.125 plus 50 times $0.625, which is about $25 plus $31, so roughly $56 per month before storage, while the PlanetScale flat fee is still $39 until you outgrow the cluster. The crossover is real, and the variable that moves it is request volume, not data size. If your traffic is low and bursty, DynamoDB is cheaper. If it is steady and heavy, the flat fee becomes the better deal, and you also escape the per-unit anxiety of watching every query.

One more honest caveat on the DynamoDB side. Strongly-consistent reads double the read cost, and every Global Secondary Index you add is billed as its own stream of writes and storage. Those two line items are where solo developers get surprised, so model them before you commit.

When to Choose PlanetScale

You want a relational database with modern developer workflow
Your data has relationships (users, orders, products, etc.)
You value the ability to migrate away from your database provider
You prefer SQL and ORM-based development
You can afford the $39/mo starting cost

When to Choose DynamoDB

You're already deep in the AWS ecosystem
Your access patterns are simple and well-defined (key-value lookups)
You need extreme scale and don't want to manage infrastructure
You're building serverless with Lambda and API Gateway
Your data model is genuinely document or key-value oriented

The Verdict

PlanetScale is the better choice for most solo developers choosing between these two. Relational data models are more flexible, SQL skills are more transferable, and you don't need to become a DynamoDB data modeling expert just to ship a feature.

But honestly? Neither is ideal. PlanetScale's $39/mo with no free tier and no foreign keys is hard to justify when Neon gives you free serverless Postgres. And DynamoDB's learning curve is overkill unless you're already living in AWS. For solo developers, start with Supabase or Neon. You'll ship faster and pay less.