Neon vs PlanetScale vs Turso: Serverless DBs 2026
Neon vs PlanetScale vs Turso: Serverless Databases for SaaS Builders 2026
Every SaaS needs a database. The old answer — provision a Postgres instance, manage connections, worry about cold starts — is increasingly obsolete for Next.js apps on Vercel. In 2026, three serverless databases dominate the indie hacker and SaaS builder conversation: Neon (serverless Postgres), PlanetScale (MySQL on Vitess), and Turso (distributed SQLite at the edge).
This guide compares all three on the criteria that actually matter for SaaS builders: pricing, cold start behavior, schema branching for CI/CD, edge runtime support, and ORM compatibility.
TL;DR
Neon for most SaaS — serverless Postgres with scale-to-zero, database branching per PR, and native Drizzle/Prisma support. The $0 free tier never expires. PlanetScale for teams that need MySQL specifically, multi-region active-active, or have an existing MySQL codebase — note the free tier was removed in 2024, minimum $39/month. Turso for edge-first apps where sub-10ms global database latency is a product requirement — distributed SQLite with Drizzle native support and 500 free databases.
Key Takeaways
- Neon: serverless Postgres, scale-to-zero, DB branching, $0 free tier, Drizzle + Prisma compatible
- PlanetScale: MySQL + Vitess, no free tier (removed 2024), $39/month minimum, best multi-region active-active
- Turso: LibSQL (SQLite fork), 35+ edge locations, 500 free DBs, Drizzle native, best for edge-deployed apps
- ORM recommendation: Drizzle for Neon/Turso (native adapters, small bundle); Prisma works with all three
- Cold starts: Neon HTTP driver ~50ms; PlanetScale HTTP driver ~80ms; Turso LibSQL ~15ms globally (edge proximity)
- Schema branching: Neon (built-in, excellent) > PlanetScale (built-in, mature) > Turso (manual, limited)
Neon: Serverless Postgres That Scales to Zero
Neon is the most popular serverless Postgres platform in the SaaS builder community, largely because of its permanent free tier and database branching feature.
Architecture
Neon separates storage and compute. Your Postgres data lives in Neon's distributed storage layer; compute (the Postgres process) spins up on demand and shuts down after a period of inactivity. This separation enables:
- Scale-to-zero: no compute = no cost. Your free tier database never sleeps unless you stop paying — it just doesn't run compute when idle.
- Instant scaling: compute scales up on demand without migrating data.
- Database branching: copy-on-write branches are near-instant because only storage metadata is copied.
Connection Setup
// Option 1: HTTP driver (recommended for serverless)
import { neon } from "@neondatabase/serverless";
import { drizzle } from "drizzle-orm/neon-http";
const sql = neon(process.env.DATABASE_URL!);
export const db = drizzle(sql);
// Option 2: WebSocket (for long-lived connections on Railway/Fly.io)
import { Pool } from "@neondatabase/serverless";
import { drizzle } from "drizzle-orm/neon-serverless";
const pool = new Pool({ connectionString: process.env.DATABASE_URL });
export const db = drizzle(pool);
The HTTP driver is critical for Vercel serverless functions — traditional TCP Postgres connections fail in serverless environments because there's no persistent connection. Neon's HTTP driver sends SQL over HTTPS, which works in any serverless context including Cloudflare Workers.
Database Branching for CI/CD
Neon's killer feature for teams:
# Each GitHub branch gets an isolated database
# Configure via Neon Dashboard → Integrations → Vercel
# Result in your preview deployment:
# DATABASE_URL=postgresql://...neon.tech/main?branch=feature/new-billing
# Migration runs against the branch database
# No production risk, no shared staging database conflicts
What branching enables:
- Run
drizzle-kit migratein CI against a branch database — never against production - Preview deployments have isolated data — no cross-PR data corruption
- Branches are automatically cleaned up when PRs are closed
Pricing 2026
| Tier | Monthly | Compute | Storage | Branches |
|---|---|---|---|---|
| Free | $0 | 0.5 vCPU-hour/month | 0.5 GB | 10 |
| Launch | $19 | 25 compute-hours | 10 GB | Unlimited |
| Scale | $69 | 750 compute-hours | 50 GB | Unlimited |
| Business | $700 | 1,000 compute-hours | 500 GB | Unlimited |
The free tier is generous for pre-revenue SaaS — 0.5 vCPU-hour/month sounds small but scale-to-zero means you only consume compute during active requests. A SaaS with 100 daily active users might use 0.1 compute-hours/month.
PlanetScale: MySQL at Scale (But No More Free Tier)
PlanetScale is built on Vitess — the same database sharding technology that powers YouTube and Slack. It's engineered for horizontal scale and multi-region deployments that Neon and Turso don't match at the high end.
The 2024 Free Tier Removal
This is the critical context for indie hackers: PlanetScale removed its free tier in March 2024. The minimum plan is now $39/month (Scaler). This fundamentally changed PlanetScale's positioning — it's no longer a startup-friendly option from day one.
For SaaS builders at the pre-revenue stage, this is usually disqualifying. $39/month is a real cost before you have a single paying customer.
Architecture
// PlanetScale serverless driver
import { connect } from "@planetscale/database";
import { drizzle } from "drizzle-orm/planetscale-serverless";
const connection = connect({
host: process.env.DATABASE_HOST!,
username: process.env.DATABASE_USERNAME!,
password: process.env.DATABASE_PASSWORD!,
});
export const db = drizzle(connection);
PlanetScale uses an HTTP-based serverless driver similar to Neon's, enabling edge and serverless compatibility.
Schema Branching
PlanetScale's schema branching predates Neon's and is more mature:
# Create a feature branch
pscale branch create your-db feature/add-organizations
# Deploy schema change
pscale deploy-request create your-db --from feature/add-organizations
# Review and merge (no-downtime migration)
pscale deploy-request deploy your-db 1
PlanetScale's deploy requests have built-in diff visualization, revert capability, and no-downtime migration using Vitess's online schema change. For complex migrations in production, this is the most mature solution of the three.
When to Choose PlanetScale
- Existing MySQL codebase: migration to Postgres is more work than staying on MySQL
- Multi-region active-active: PlanetScale's Vitess architecture handles global write conflict resolution that Postgres doesn't natively support
- Need PlanetScale's schema branching maturity: deploy requests with visual diffs and no-downtime rollbacks
- $39/month is justified: you have revenue or funding
Pricing 2026
| Tier | Monthly | Rows Read | Rows Written | Storage |
|---|---|---|---|---|
| Scaler | $39 | 100B/month | 50M/month | 10 GB |
| Scaler Pro | $299 | 1T/month | 500M/month | 100 GB |
| Enterprise | Custom | Custom | Custom | Custom |
Turso: SQLite Distributed at the Edge
Turso is the most architecturally different option. Instead of running a centralized database in one region, Turso replicates SQLite databases to 35+ edge locations globally. Your database query runs in the region closest to your user.
Architecture
Turso uses LibSQL — a fork of SQLite with added features: replication, remote connections, and a HTTP API. Key implications:
- Read latency is globally low: if your user is in Tokyo, they query the Tokyo replica, not a US database
- SQLite limitations apply: no concurrent writes, no complex transactions, column type flexibility (SQLite is loosely typed)
- Per-database model: Turso's pricing is per database — you can have thousands of isolated databases cheaply
Connection Setup
// Turso with Drizzle (native support)
import { createClient } from "@libsql/client";
import { drizzle } from "drizzle-orm/libsql";
const client = createClient({
url: process.env.TURSO_DATABASE_URL!,
authToken: process.env.TURSO_AUTH_TOKEN!,
});
export const db = drizzle(client);
No special adapter needed — Drizzle has native LibSQL support that's been production-stable since v0.28.
Multi-Tenant Architecture with Turso
Turso's per-database model enables a powerful multi-tenancy pattern:
// One database per organization (tenant isolation at the DB layer)
async function getOrgDatabase(orgSlug: string) {
const url = `libsql://${orgSlug}-${process.env.TURSO_ORG}.turso.io`;
const client = createClient({
url,
authToken: process.env.TURSO_AUTH_TOKEN!,
});
return drizzle(client);
}
// API route: each request hits the organization's own database
// Zero cross-tenant data leakage at the infrastructure level
This pattern gives you Shopify-style database isolation (each tenant has their own database) at SQLite costs — dramatically cheaper than running a Postgres instance per tenant.
Edge Deployment
// Turso in Cloudflare Workers
// wrangler.toml:
// [vars]
// TURSO_DATABASE_URL = "libsql://..."
// TURSO_AUTH_TOKEN = "..."
export default {
async fetch(request, env) {
const client = createClient({
url: env.TURSO_DATABASE_URL,
authToken: env.TURSO_AUTH_TOKEN,
});
const db = drizzle(client);
const users = await db.select().from(usersTable).limit(10);
return Response.json(users);
},
};
Query from a Cloudflare Worker → hits the nearest Turso replica → sub-20ms database round-trip.
SQLite Limitations
Before choosing Turso, understand what SQLite doesn't do well:
✗ Concurrent writes (SQLite serializes writes — high-write workloads bottleneck)
✗ Complex joins on large datasets (Postgres query planner is more sophisticated)
✗ Full-text search at scale (Postgres has better FTS primitives)
✗ Stored procedures (SQLite has limited function support)
✗ Column-level types are flexible (SQLite accepts any value in any column)
✓ Simple CRUD at high read volume
✓ Per-tenant isolation (cheap per-database model)
✓ Edge-deployed apps with global read requirements
✓ Applications where Cloudflare D1 compatibility is needed
Pricing 2026
| Tier | Monthly | Databases | Row reads | Row writes | Storage |
|---|---|---|---|---|---|
| Free | $0 | 500 | 1B/month | 25M/month | 5 GB |
| Starter | $29 | 10,000 | 100B/month | 1B/month | 25 GB |
| Scaler | $599 | Unlimited | Unlimited | Unlimited | 1 TB |
The free tier's 500 database limit enables the per-tenant-database pattern for early-stage multi-tenant SaaS — 500 organizations at $0/month.
Head-to-Head Comparison
| Feature | Neon | PlanetScale | Turso |
|---|---|---|---|
| DB Engine | PostgreSQL | MySQL (Vitess) | SQLite (LibSQL) |
| Free tier | ✓ Permanent | ✗ Removed 2024 | ✓ 500 DBs |
| Min paid | $19/month | $39/month | $29/month |
| Serverless | ✓ HTTP driver | ✓ HTTP driver | ✓ HTTP/WebSocket |
| Edge support | ✓ Cloudflare, Workers | ✓ | ✓ Native (35+ regions) |
| DB branching | ✓ Excellent | ✓ Mature (deploy requests) | ✗ Manual |
| Drizzle adapter | ✓ neon-http | ✓ planetscale-serverless | ✓ libsql |
| Prisma adapter | ✓ Accelerate | ✓ | ✓ Preview |
| Per-tenant DBs | Limited by cost | Limited by cost | ✓ 500 free |
| Global read latency | Single region | Multi-region available | Sub-20ms (edge) |
| Write performance | Strong | Strong (Vitess) | Limited (SQLite serial) |
| Complex queries | Excellent (Postgres) | Good (MySQL) | Limited (SQLite) |
Decision Framework
Choose Neon if:
- New Next.js SaaS on Vercel (the default for 2026)
- You want Postgres semantics and the full ecosystem
- Database branching per PR is important for your CI/CD
- Pre-revenue (free tier is permanent and sufficient)
- Drizzle or Prisma is your ORM
Choose PlanetScale if:
- Existing MySQL codebase migrating to serverless
- Multi-region active-active writes are required ($500K+ ARR use case)
- You have $39/month budget from day one
- Need PlanetScale's mature schema branching with visual diffs and no-downtime rollback
Choose Turso if:
- Edge-first app on Cloudflare Workers where global read latency is a core product requirement
- Multi-tenant SaaS where per-tenant database isolation reduces complexity (Turso's per-DB model)
- Simple CRUD workloads with high global read volume and low write contention
- Cloudflare D1 compatibility is needed (same SQLite family)
See the full Drizzle vs Prisma serverless guide for ORM setup with each database. Browse boilerplates with Neon and Turso-powered starters on StarterPick.