PlanetScale vs Supabase
PlanetScale and Supabase both answer the same question: where does your data live? Managed MySQL built on Vitess, aimed at teams that expect serious scale and want schema changes without downtime. Managed Postgres bundled with auth, storage, realtime and an auto-generated REST and client API. Supabase covers more of the ecosystem, so it survives a change of framework; PlanetScale is the better fit while you stay where it is strongest.
Verdict
Supabase covers more of the ecosystem, so it survives a change of framework; PlanetScale is the better fit while you stay where it is strongest.
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.
Pick Supabase if
- ✓Real Postgres underneath, so extensions, SQL and standard tooling all apply.
- ✓Auth, storage and realtime included, which removes several vendor decisions at once.
- ✓Client libraries let simple apps query straight from the browser safely.
| Comparison | PlanetScale | Supabase |
|---|---|---|
| Pricing shape | Paid plans priced by cluster size and usage, positioned at production workloads rather than hobby projects. | Free tier for hobby projects, then a flat per-project fee plus usage for compute, storage and bandwidth. |
| Frameworks | Next.js, SvelteKit, Nuxt, Laravel, Rails, Django | Next.js, SvelteKit, Nuxt, React Native, Expo, Flutter |
| In one line | Managed MySQL built on Vitess, aimed at teams that expect serious scale and want schema changes without downtime. | Managed Postgres bundled with auth, storage, realtime and an auto-generated REST and client API. |
Pricing described qualitatively because published plans change often. Checked 2026-08-23. Confirm current terms on PlanetScale and Supabase.
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.
Supabase
Strengths
- ✓Real Postgres underneath, so extensions, SQL and standard tooling all apply.
- ✓Auth, storage and realtime included, which removes several vendor decisions at once.
- ✓Client libraries let simple apps query straight from the browser safely.
- ✓Open source core, so self-hosting is a genuine escape hatch.
Tradeoffs
- ✗Querying from the client pushes authorization into policies that are easy to misconfigure.
- ✗The bundled services encourage coupling that is painful to untangle later.
- ✗Dashboard-driven changes can drift from what is in your migration files.
- ✗Connection pooling behaviour surprises people moving from a classic long-lived server.
Frequently asked questions
Is PlanetScale or Supabase better?
Neither is better in the abstract. Supabase covers more of the ecosystem, so it survives a change of framework; PlanetScale is the better fit while you stay where it is strongest. Pick the one whose downside you can absorb, because both upsides are real.
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.
What is the main drawback of Supabase?
Querying from the client pushes authorization into policies that are easy to misconfigure. The bundled services encourage coupling that is painful to untangle later.
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. Plan for it in the data model, not in the framework, and the switch stays survivable.