Neon vs PlanetScale
Neon and PlanetScale are both serverless databases but they target different worlds. Neon is Postgres with branching and autoscale, great for AI apps, Next.js, and preview environments. PlanetScale is MySQL with Vitess-scale sharding, great for legacy migrations and huge write workloads. Most AI-era startups want Postgres, so Neon wins the majority.
Two products, side by side.
Serverless Postgres with autoscale and branching
- Full Postgres (SQL, transactions, extensions, joins)
- Git-like branching
- Autoscale + scale-to-zero
- pgvector for AI
- Point-in-time recovery
- Postgres write throughput ceiling higher than PlanetScale MySQL at extreme scale
- Newer product
Serverless MySQL with Vitess-based horizontal scale
- Massive horizontal scale (Vitess under the hood)
- Deploy request workflow for schema changes
- Zero-downtime schema changes
- Boost cache
- MySQL, not Postgres (no arrays, no JSONB, no pgvector natively)
- No foreign keys by default (Vitess constraint)
- Killed hobby-tier in 2024, minimum $39/mo now
- Weaker fit for AI workloads
Neon vs PlanetScale on the specs.
| Feature | Neon | PlanetScale |
|---|---|---|
| Database engine | ✓Postgres 17 | MySQL 8 (via Vitess) |
| Foreign keys | ✓Full support | Disabled by default (Vitess) |
| JSONB / arrays | ✓Yes | JSON only, no arrays |
| Vector search (AI) | ✓pgvector built in | Requires external |
| Branching | Yes | Yes (deploy request workflow) |
| Horizontal shard | Vertical + read replicas | ✓Yes (Vitess-native) |
| Free tier | ✓Yes (0.5 GB, autoscale) | No hobby tier since 2024 |
| Zero-downtime schema | Manual (pg-osc or similar) | ✓Native deploy requests |
| Postgres extensions | ✓Wide (pgvector, PostGIS, TimescaleDB) | MySQL only |
What you will actually pay.
| Tier | Neon | PlanetScale |
|---|---|---|
| Free / entry | $0 | $39 / mo (Scaler) |
| Pro | $19 / mo (10 GB + 300 CU-h) | $99 / mo (Scaler Pro, 500 GB) |
| Enterprise | Scale $69+ / mo usage | Enterprise pricing |
Which one should you pick?
Building a Next.js / TypeScript app, need Postgres features (JSONB, pgvector, arrays, real foreign keys), want preview-per-PR databases, or shipping AI features that need vector search.
Migrating from an existing MySQL app, need Vitess-scale horizontal writes, or your team is deeply MySQL-native and does not want to relearn Postgres.
For a mid-scale SaaS with < 5k writes/sec, either handles the load. Neon's ecosystem is more active for modern Node / Deno / edge stacks.
Related matchups.
Common questions.
Which is faster?
For point reads and writes at small-to-mid scale, both are microseconds difference. PlanetScale scales writes horizontally further; Neon's autoscale handles read spikes elastically.
Which works better with Vercel / Cloudflare edge?
Neon has the tighter integration, Vercel-Neon partnership, HTTP driver for edge functions. PlanetScale works with edge too via their serverless driver.
Can I use Prisma or Drizzle?
Both are supported. Drizzle has first-class Neon serverless driver support. Prisma works on both with connection pooling.
Which is better for AI apps?
Neon, because of pgvector. AI apps need vector search for RAG, and Postgres + pgvector is the standard combo.
Do either offer preview databases per PR?
Both. Neon has cheap branches; PlanetScale has deploy requests. Neon is more ergonomic for spin-up-per-PR patterns.
Open the tool.
Once you have picked, grade your stack across 10 production categories in 3 minutes. Free, honest, prioritised fix plan.
Grade the Neon or PlanetScale setup you pick