Neon vs PlanetScale
Neon and PlanetScale both answer the same question: where does your data live? Serverless Postgres that separates storage from compute, so branches of your database work like branches of your code. Managed MySQL built on Vitess, aimed at teams that expect serious scale and want schema changes without downtime. Neon bills against what you actually use, which is kind early and needs watching later; PlanetScale is more predictable and less forgiving of a quiet month.
Verdict
Neon bills against what you actually use, which is kind early and needs watching later; PlanetScale is more predictable and less forgiving of a quiet month.
Pick Neon if
- ✓Database branching gives every pull request a realistic copy of production data.
- ✓Compute scales to zero, so idle side projects cost almost nothing.
- ✓Plain Postgres wire protocol, so any existing driver or ORM connects unchanged.
Pick PlanetScale if
- ✓Non-blocking schema changes reviewed like code before they hit production.
- ✓Vitess sharding means the growth path to very large tables already exists.
- ✓Deploy requests give schema migrations an approval workflow teams actually follow.
| Comparison | Neon | PlanetScale |
|---|---|---|
| Pricing shape | Free tier with limited storage and compute hours, then usage-based billing for compute time and stored data. | Paid plans priced by cluster size and usage, positioned at production workloads rather than hobby projects. |
| Frameworks | Next.js, SvelteKit, Nuxt, Laravel, Django, Rails | Next.js, SvelteKit, Nuxt, Laravel, Rails, Django |
| In one line | Serverless Postgres that separates storage from compute, so branches of your database work like branches of your code. | Managed MySQL built on Vitess, aimed at teams that expect serious scale and want schema changes without downtime. |
Pricing described qualitatively because published plans change often. Checked 2026-08-23. Confirm current terms on Neon and PlanetScale.
Neon
Strengths
- ✓Database branching gives every pull request a realistic copy of production data.
- ✓Compute scales to zero, so idle side projects cost almost nothing.
- ✓Plain Postgres wire protocol, so any existing driver or ORM connects unchanged.
- ✓Point-in-time restore falls out of the storage design rather than being bolted on.
Tradeoffs
- ✗Scale to zero means the first query after idle pays a cold start.
- ✗Storage and compute separation adds latency compared to a local disk.
- ✗It is only the database, so auth, storage and jobs stay your problem.
- ✗Branch sprawl needs its own cleanup discipline once a team gets going.
PlanetScale
Strengths
- ✓Non-blocking schema changes reviewed like code before they hit production.
- ✓Vitess sharding means the growth path to very large tables already exists.
- ✓Deploy requests give schema migrations an approval workflow teams actually follow.
- ✓Insights surface slow queries without wiring up a separate monitoring stack.
Tradeoffs
- ✗Foreign key constraints were historically restricted, which shapes how you model data.
- ✗MySQL rather than Postgres, so Postgres-specific extensions and types are unavailable.
- ✗Priced for real workloads, so small projects subsidise capacity they never use.
- ✗The Vitess layer adds behaviour that differs subtly from stock MySQL.
Frequently asked questions
Is Neon or PlanetScale better?
Neither is better in the abstract. Neon bills against what you actually use, which is kind early and needs watching later; PlanetScale is more predictable and less forgiving of a quiet month. The wrong choice here is usually recoverable, so weight speed of decision over certainty.
What is the main drawback of Neon?
Scale to zero means the first query after idle pays a cold start. Storage and compute separation adds latency compared to a local disk.
What is the main drawback of PlanetScale?
Foreign key constraints were historically restricted, which shapes how you model data. MySQL rather than Postgres, so Postgres-specific extensions and types are unavailable.
Can you switch from one to the other later?
Usually, at a cost that grows with how much of your product leans on the database layer. The sooner you wrap it in your own interface, the cheaper the exit stays.