Neon vs PlanetScale vs Turso: Serverless Database Comparison 2026

Serverless databases have changed how modern applications handle data. Instead of managing a PostgreSQL server or paying for always-on compute, you can connect directly from edge functions, scale to zero between requests, and branch your database like you branch your code.

Three platforms dominate this space in 2026: Neon (serverless Postgres), PlanetScale (serverless MySQL), and Turso (distributed SQLite). This guide breaks down each one so you can pick the right tool.

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The Quick Answer

	Neon	PlanetScale	Turso
Engine	PostgreSQL 16	MySQL 8	SQLite (libSQL)
Free tier	0.5 GB storage, 190h compute	5 GB storage, 1B row reads	9 GB storage, 500 DBs
Branching	✅	✅	✅
Edge reads	❌	❌	✅
Global replicas	Read replicas	PlanetScale Boost	21+ regions
Connection pooling	Built-in (PgBouncer)	Built-in	Built-in
Prisma/Drizzle	✅	✅	✅
Best for	Postgres workloads, Next.js	High-write MySQL apps	Edge-native apps

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Neon: Serverless PostgreSQL

What Is Neon?

Neon separates PostgreSQL compute from storage. Storage lives on S3-compatible object storage; compute (the Postgres process) scales to zero when idle and starts in ~500ms. You get a full PostgreSQL 16 database with all extensions, stored procedures, and standard tooling.

Pricing (2026)

• Free: 0.5 GB storage, 190 compute hours/month, 1 project, branching included
• Launch ($19/mo): 10 GB storage, unlimited compute hours, 10 projects
• Scale ($69/mo): 50 GB storage, read replicas, more projects
• Business ($700+): custom SLA, dedicated support

Compute is billed per second when active — you only pay for queries running.

Branching

Neon’s killer feature: branch your database instantly with copy-on-write semantics.

# Neon CLI
neon branch create --name feature/new-schema --parent main

# Runs against isolated branch DB
DATABASE_URL=postgres://...branch-endpoint... npx prisma migrate dev

# Merge is done via promoting the schema back to main
# (data merging is handled by your migration scripts)

Branches share the parent’s storage and only diff diverges — branching is instant regardless of database size. Ideal for:

• Feature branches that need their own test data
• CI/CD pipelines (each PR gets a fresh branch)
• Canary testing schema changes

Cold Start

Neon’s biggest limitation is cold start latency. After the compute scales to zero (default: 5 minutes idle), the first query takes ~500ms–1s to wake the instance.

Mitigation:

• Increase the autosuspend delay (paid tiers)
• Use connection pooling endpoint (scales independently)
• Keep warm with periodic lightweight queries

// Neon's recommended connection setup
import { neon } from "@neondatabase/serverless";

const sql = neon(process.env.DATABASE_URL!);

// For HTTP-based queries (lower cold start overhead than TCP)
const users = await sql`SELECT * FROM users WHERE active = true`;

When to Use Neon

• You need full PostgreSQL (arrays, JSONB, PostGIS, pgvector)
• You’re deploying to Vercel/Netlify (tight Neon integration)
• Your team already knows Postgres
• You want git-like branching for database workflows
• You have bursty, unpredictable traffic patterns

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PlanetScale: Serverless MySQL with Vitess

What Is PlanetScale?

PlanetScale runs MySQL on top of Vitess — the same sharding middleware YouTube uses. Vitess enables horizontal scaling across shards, non-blocking schema changes, and database branching.

Pricing (2026)

• Hobby (free): 5 GB storage, 1B row reads/mo, 10M row writes/mo, 1 database
• Scaler ($29/mo): 10 GB storage, 10B row reads, 100M row writes, branching
• Scaler Pro: from $39/mo + usage, HIPAA compliance, private connections
• Enterprise: custom pricing

Branching and Schema Workflows

PlanetScale’s branching maps directly to safe schema deployments:

# Create a branch for a schema change
pscale branch create mydb add-user-indexes

# Connect to branch
pscale connect mydb add-user-indexes --port 3309

# Apply migration
DATABASE_URL="mysql://[email protected]:3309/mydb" npx prisma db push

# Open a deploy request (like a PR, but for schema)
pscale deploy-request create mydb add-user-indexes

# After review, merge — PlanetScale applies it with zero downtime
pscale deploy-request deploy mydb 1

The non-blocking schema change is PlanetScale’s standout technical feature: adding indexes, changing column types, and renaming columns happen without table locks.

Boost: Read Caching Layer

PlanetScale Boost is an in-memory query cache that sits between your app and the database. Queries that hit the cache return in sub-millisecond time.

// No code changes needed — configure in dashboard
// Queries with deterministic results are cached automatically
const users = await db.execute("SELECT * FROM users WHERE id = ?", [id]);
// If cached: ~0.1ms. If not: normal MySQL latency.

Limitations

• No foreign keys (Vitess limitation) — use application-level referential integrity
• MySQL dialect only — not drop-in compatible with Postgres
• The free “Hobby” tier was removed in 2024 (then partially restored) — check current pricing

When to Use PlanetScale

• You need MySQL (Laravel, Rails, existing MySQL apps)
• Zero-downtime schema changes are critical
• Horizontal sharding at massive scale (Vitess-backed)
• Teams that want branching + deploy requests as a governance workflow

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Turso: Distributed SQLite at the Edge

What Is Turso?

Turso is built on libSQL (an open-source SQLite fork) and runs SQLite databases distributed across 21+ PoPs globally. Instead of one central database, each user’s data lives close to them.

Pricing (2026)

• Free: 9 GB total storage, 500 databases, 1B row reads, 25M row writes, embedded replicas
• Scaler ($29/mo): 24 GB storage, 10k databases, unlimited reads, 100M writes
• Pro ($59/mo): 50 GB storage, unlimited DBs, groups (multi-region placement)

Turso’s free tier is exceptionally generous — most indie projects and side projects never pay.

The Architecture

Turso’s architecture is unique:

1. Primary database — one region (your choice), handles all writes
2. Replicas — read-only copies in other regions, synced in near-real-time
3. Embedded replicas — SQLite DB running inside your serverless function, synced from Turso

User in Tokyo → Reads from Tokyo replica (~5ms)
User in NY    → Reads from NY replica (~5ms)
Write anywhere → Routed to primary → Replicated globally

Connection and Query

import { createClient } from "@libsql/client";

const db = createClient({
  url: process.env.TURSO_DATABASE_URL!,
  authToken: process.env.TURSO_AUTH_TOKEN!,
});

// Standard SQL
const result = await db.execute("SELECT * FROM users WHERE id = ?", ["123"]);
console.log(result.rows);

// Batch (atomic)
await db.batch([
  { sql: "INSERT INTO users (name) VALUES (?)", args: ["Alice"] },
  { sql: "INSERT INTO audit_log (action) VALUES (?)", args: ["user.create"] },
]);

// Transactions
const tx = await db.transaction("write");
try {
  await tx.execute("UPDATE accounts SET balance = balance - ? WHERE id = ?", [100, "alice"]);
  await tx.execute("UPDATE accounts SET balance = balance + ? WHERE id = ?", [100, "bob"]);
  await tx.commit();
} catch (e) {
  await tx.rollback();
}

Embedded Replicas (Game Changer)

Turso’s embedded replicas run SQLite inside your application process — reads are literally nanoseconds, not network calls.

import { createClient } from "@libsql/client";

const db = createClient({
  url: "file:./local.db", // local SQLite file
  syncUrl: process.env.TURSO_DATABASE_URL!, // remote Turso DB
  authToken: process.env.TURSO_AUTH_TOKEN!,
  syncInterval: 60, // sync every 60 seconds
});

// Reads hit local SQLite — sub-millisecond
const users = await db.execute("SELECT * FROM users");

// Writes go to remote Turso, then sync back
await db.execute("INSERT INTO users (name) VALUES (?)", ["Alice"]);

This pattern is ideal for Cloudflare Workers with D1-style local caching, or applications where read latency is critical.

Multi-Database Architecture

Turso supports 500 (free) to unlimited (paid) databases. This unlocks a database-per-tenant pattern that’s practically impossible with traditional Postgres:

// Each customer gets their own isolated SQLite database
const getDbForTenant = (tenantId: string) =>
  createClient({
    url: `libsql://${tenantId}-myapp.turso.io`,
    authToken: getTokenForTenant(tenantId),
  });

Benefits:

• Complete data isolation per tenant
• No cross-tenant query interference
• Simpler backup/restore per tenant
• GDPR deletion is just deleting a database

Turso Limitations

• SQLite dialect — no stored procedures, limited JOIN performance for very complex queries
• Single-writer — writes go through the primary (no multi-master)
• No JSONB, PostGIS — SQLite JSON functions are simpler than Postgres
• Schema migrations — no native branching, use external tools (Drizzle migrations, Flyway)

When to Use Turso

• Building edge-first applications (Cloudflare Workers, Deno Deploy)
• Multi-tenant SaaS — database-per-tenant without cost explosion
• Read-heavy global apps — embedded replicas or regional reads
• Mobile/offline apps — embedded SQLite that syncs to cloud
• Side projects — generous free tier, SQLite simplicity

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Head-to-Head Comparison

Latency

Scenario	Neon	PlanetScale	Turso
Cold start	500ms–1s	Near-zero	Near-zero
Warm query (same region)	2–10ms	2–10ms	2–10ms
Warm query (cross-region)	50–200ms	50–200ms	2–10ms (replica)
Embedded replica read	N/A	N/A	<1ms

Migration Workflow

# Neon — standard Postgres migrations
npx prisma migrate dev --name add-user-indexes
# Deploy: branch → migrate → merge branch

# PlanetScale — deploy requests
pscale branch create mydb add-indexes
# ... apply migration to branch ...
pscale deploy-request create mydb add-indexes
pscale deploy-request deploy mydb 1

# Turso — run SQL migrations manually or via Drizzle/Flyway
npx drizzle-kit push # pushes schema to Turso DB

ORM Support

All three work well with popular ORMs:

// Prisma + Neon
generator client { provider = "prisma-client-js" }
datasource db { provider = "postgresql"; url = env("DATABASE_URL") }

// Prisma + PlanetScale
datasource db {
  provider     = "mysql"
  url          = env("DATABASE_URL")
  relationMode = "prisma" // required (no FK support in Vitess)
}

// Drizzle + Turso
import { drizzle } from "drizzle-orm/libsql";
import { createClient } from "@libsql/client";

const client = createClient({ url: process.env.TURSO_URL!, authToken: process.env.TURSO_TOKEN! });
const db = drizzle(client);

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Decision Framework

Do you need PostgreSQL features (JSONB, arrays, PostGIS, pgvector)?
  → Neon

Do you need MySQL compatibility (Laravel, Rails, existing MySQL)?
  → PlanetScale

Do you need edge-native reads or database-per-tenant?
  → Turso

Do you have bursty traffic and need scale-to-zero?
  → Neon or Turso (both scale to zero)

Do you need non-blocking schema migrations at scale?
  → PlanetScale

Is free tier important for side projects?
  → Turso (most generous), then Neon

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Summary

In 2026, there’s no single “best” serverless database — it depends on your stack and requirements:

• Neon is the best choice for Postgres shops. Full PostgreSQL with branching and Vercel integration. Cold starts are a trade-off for scale-to-zero.
• PlanetScale excels at high-write MySQL workloads with zero-downtime schema changes. Best if you’re already in the MySQL ecosystem.
• Turso is the edge-native choice. Embedded replicas, 500 free databases, and SQLite simplicity make it ideal for edge functions, multi-tenant SaaS, and read-heavy global apps.

The good news: all three have solid free tiers. You can try all three for your specific workload before committing.