About 21; min
Neon and PlanetScale are the two hottest serverless database platforms in 2026. Both promise auto-scaling, branching, and pay-per-use pricing that traditional managed databases can’t match. But they use different engines — Neon runs PostgreSQL, PlanetScale runs MySQL (Vitess). The choice affects your application architecture, not just your bill.
Quick Pricing Comparison
| Plan | Neon | PlanetScale |
|---|---|---|
| Free | 512 MB storage, 191 compute hours | 5 GB storage, 1B row reads/mo |
| Launch/Scaler | $19/mo | $39/mo |
| Scale/Pro | $69/mo | $99/mo |
| Enterprise | Custom | Custom |
Neon is cheaper at every tier: $19 vs $39, $69 vs $99. PlanetScale includes more free storage (5 GB vs 512 MB) but Neon’s compute model gives you more flexibility.
Neon Pricing Deep Dive
Neon’s pricing revolves around “compute hours” — the time your database is actively processing queries. When no queries are running, Neon auto-suspends your compute to zero (and zero cost). This means a database that’s active 8 hours/day uses roughly 240 compute hours/month — well within the Launch plan’s 300 hours.
Neon’s Killer Features
- Branching: Create a full copy of your database in seconds for development, testing, or preview environments. Branches use copy-on-write storage, so a 10 GB production database branch costs near-zero until you modify data. This replaces expensive staging databases
- Auto-scaling to zero: No queries = no compute charges. Perfect for development databases, staging environments, and low-traffic apps that don’t need 24/7 availability
- Serverless driver: Connect from serverless functions (Vercel, Cloudflare Workers) over HTTP — no persistent connection pooling needed. Traditional PostgreSQL requires connection pooling (PgBouncer) for serverless, adding complexity
- pgvector: Built-in vector extension for AI embeddings. Store and query embeddings alongside your relational data without a separate vector database
Neon’s Gotchas
- Cold starts: Auto-suspended databases take 500ms–2s to wake up on the first query. For always-on production apps, configure auto-suspend to “never” (uses more compute hours)
- Compute hour limits: If your database is active 24/7, you need ~720 compute hours/month. Launch (300 hours) isn’t enough — you’d need Scale ($69) or buy additional hours at $0.16/hour
- Storage scaling: Overage beyond plan limits costs $3.50/GB on Launch, $1.75/GB on Scale. Less competitive than PlanetScale’s included storage
PlanetScale Pricing Deep Dive
PlanetScale charges by row reads and writes instead of compute hours. This makes costs predictable for applications with consistent query patterns but unpredictable for apps with variable workloads.
PlanetScale’s Killer Features
- Deploy requests: Schema changes go through a pull-request-like workflow. Review, approve, and apply migrations without downtime. No other managed database offers this workflow natively
- Horizontal sharding (Vitess): PlanetScale runs on Vitess (YouTube’s database technology). When you outgrow a single database, PlanetScale can shard your data across multiple servers without application changes. Neon (PostgreSQL) doesn’t support native horizontal sharding
- PlanetScale Boost: Query caching that sits between your app and database. Frequently executed queries are cached and served in microseconds. Reduces database load by 80–90% for read-heavy applications
- Insights: Built-in query analytics showing slow queries, query frequency, and index recommendations. Replaces the need for separate tools like pganalyze or Datadog’s database monitoring
PlanetScale’s Gotchas
- No foreign keys: PlanetScale (Vitess) doesn’t support foreign key constraints. Referential integrity must be enforced at the application level. This is a dealbreaker for teams that rely on database-level constraints
- MySQL only: If your ORM, migration tools, or team expertise is PostgreSQL, switching to PlanetScale means rewriting queries and learning MySQL differences
- Row read counting: Every indexed lookup, join, and scan counts toward your read limit. A poorly written query that scans 1M rows costs 1M reads. Monitor query efficiency carefully
Cost Comparison
Small app (light usage, 2 GB data)
| Provider | Plan | Monthly |
|---|---|---|
| Neon | Free (512 MB) or Launch ($19) | $0–$19 |
| PlanetScale | Free (5 GB) | $0 |
| Supabase | Free (500 MB) or Pro ($25) | $0–$25 |
PlanetScale’s 5 GB free tier is the most generous for small apps. Neon’s 512 MB free tier fills up quickly but the auto-suspend means zero compute costs when inactive.
Growing app (20 GB data, moderate queries, always-on)
| Provider | Plan | Monthly |
|---|---|---|
| Neon Scale | $69 + storage overage | ~$85 |
| PlanetScale Scaler | $39 + storage overage | ~$55 |
| AWS RDS (db.t4g.medium) | On-demand | ~$65 |
Production app (100 GB data, heavy queries, high availability)
| Provider | Plan | Monthly |
|---|---|---|
| Neon Scale + overages | $69 + ~$88 storage + compute | ~$200 |
| PlanetScale Scaler Pro + overages | $99 + ~$75 storage | ~$200 |
| AWS RDS (db.r6g.large, Multi-AZ) | On-demand | ~$450 |
At production scale, Neon and PlanetScale cost roughly the same (~$200/month) and both significantly undercut traditional managed databases like RDS ($450/month for equivalent specs with high availability).
Feature Comparison
| Feature | Neon | PlanetScale |
|---|---|---|
| Engine | PostgreSQL | MySQL (Vitess) |
| Foreign keys | Yes (full support) | No |
| Branching | Instant (copy-on-write) | Yes (deploy requests) |
| Schema migration workflow | Manual (standard migrations) | Deploy requests (PR-like review) |
| Auto-scaling | Scale to zero + up | Read replicas + sharding |
| Horizontal sharding | No (PostgreSQL limitation) | Yes (Vitess native) |
| Serverless driver | Yes (HTTP + WebSocket) | Yes (HTTP) |
| Vector search (AI) | pgvector (built-in) | No native support |
| Query caching | No | PlanetScale Boost |
| Point-in-time restore | 7–14 days | 30 days (Scaler Pro) |
| Connection pooling | Built-in | Built-in |
| Read replicas | Scale plan | Scaler Pro |
| Extensions | 50+ PostgreSQL extensions | Limited MySQL plugins |
PostgreSQL vs MySQL: The Real Decision
Choosing between Neon and PlanetScale is really choosing between PostgreSQL and MySQL. This isn’t a pricing decision — it’s a technical one:
Choose PostgreSQL (Neon) If:
- Your team has PostgreSQL expertise and your ORM is configured for it
- You need foreign key constraints for data integrity
- pgvector for AI embeddings is part of your stack
- You use PostgreSQL extensions (PostGIS, pg_trgm, hstore, jsonb operators)
- Your app framework defaults to PostgreSQL (Rails, Django, Next.js community)
Choose MySQL (PlanetScale) If:
- You need horizontal sharding for massive scale (Vitess handles billions of rows)
- Deploy requests (schema change review) would improve your migration workflow
- Query caching (Boost) would significantly reduce your database load
- Your existing app uses MySQL and migration to PostgreSQL isn’t worth the effort
- You’re building at YouTube/Slack scale where Vitess’s sharding matters
Best for most web apps: Neon — PostgreSQL is the default database for modern web development. Branching, auto-scaling to zero, and pgvector for AI make Neon the best serverless PostgreSQL available.
Best for massive scale: PlanetScale — Vitess-powered horizontal sharding handles workloads that PostgreSQL can’t scale to without complex partitioning. If you’re building for billions of rows, PlanetScale is the answer.
Best free tier: PlanetScale (5 GB + 1B reads) for storage volume. Neon for development flexibility (branching + auto-suspend).
Best for AI apps: Neon — pgvector stores embeddings alongside relational data. No separate vector database needed.
Best schema management: PlanetScale — deploy requests bring code review practices to database migrations. Nothing else matches this workflow.
FAQ
Can I migrate from one to the other?
Moving between PostgreSQL and MySQL is a significant effort — different SQL dialects, data types, and ORM configurations. Budget 1–3 weeks for a medium-complexity application. Use pgloader (MySQL→PostgreSQL) or AWS DMS for the data migration itself.
Should I use these instead of Supabase?
Supabase bundles PostgreSQL with auth, storage, and real-time features. If you need just a database, Neon or PlanetScale offer better database-specific features (branching, sharding, serverless scaling). If you need a full backend, Supabase is more complete.
Are these production-ready?
Yes. Both power thousands of production applications. Neon has SOC2 certification. PlanetScale has SOC2 on Scaler Pro. Both offer point-in-time recovery and automated backups. For mission-critical workloads, use paid plans with read replicas and HA configuration.
What about CockroachDB or TiDB?
CockroachDB (PostgreSQL-compatible) and TiDB (MySQL-compatible) are distributed databases that offer horizontal scaling like PlanetScale but with stronger consistency guarantees. They’re more expensive and complex — best for teams that need global distribution and strong consistency simultaneously.
