PlanetScale vs Turso(2026)
PlanetScale is better for teams that need non-blocking schema changes. Turso is the stronger choice if ultra-low latency at edge. PlanetScale is paid (from $39/month) and Turso is freemium (from $29/month).
Full feature breakdown, pricing details, and pros & cons below.
By Bikram NathLast updated
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PlanetScale
PlanetScale is a MySQL-compatible serverless database with branching workflows for schema changes.
Starting at $39/month
Visit PlanetScaleTurso
Turso is a distributed SQLite database built for the edge, powered by libSQL.
Starting at $29/month
Visit TursoHow Do PlanetScale and Turso Compare on Features?
| Feature | PlanetScale | Turso |
|---|---|---|
| Pricing model | paid | freemium |
| Starting price | $39/month | $29/month |
| MySQL-compatible | ✓ | — |
| Database branching | ✓ | — |
| Non-blocking schema changes | ✓ | — |
| Query insights | ✓ | — |
| Replication | ✓ | — |
| Distributed SQLite | — | ✓ |
| Edge-first | — | ✓ |
| libSQL fork | — | ✓ |
| Multi-tenancy | — | ✓ |
| Embedded replicas | — | ✓ |
PlanetScale Pros and Cons vs Turso
PlanetScale
Turso
Deep dive: PlanetScale
When to choose PlanetScale
Choose PlanetScale if you're a MySQL shop or need non-blocking schema changes without downtime. Deployments with schema migrations run asynchronously while reads and writes continue—a genuine advantage over RDS MySQL, which blocks during ALTER TABLE. The branch and pull-request workflow for schema changes is polished, making deployments safer and faster for teams doing weekly or daily releases. Ideal for MySQL-native teams scaling to high traffic. PlanetScale is wrong if you need foreign key constraints (disabled by default for horizontal scaling), you're on a tight budget (no free tier since 2024; minimum $39/month), or you need multi-region write replicas without architecture complexity. Projects that relied on PlanetScale's free tier in 2023 now have nowhere to go—Firebase or Turso become alternatives. Also wrong if you plan to migrate off MySQL later; PlanetScale's schema changes rely on disabled foreign keys, so migrating to Postgres requires rearchitecting your data model. Teams heavily invested in normalized relational schemas with FX constraints should stay on PostgreSQL.
Real-world use case
A B2B SaaS team (~8 engineers) managing a high-traffic invoice platform (2 million monthly transactions) does weekly schema deployments on PlanetScale. One Wednesday at 2pm, they added an index to a 2TB table. Historically on RDS MySQL, this 4-6 minute lock would've cost ~$1,200 in lost transactions. On PlanetScale, the index built asynchronously in 8 minutes with zero downtime. Cost: $99/month. Real tradeoff: PlanetScale recommends disabling foreign keys for sharding, so they removed them. That decision required adding application-level validation to backfill constraints—one engineer spent a week on this. They chose PlanetScale over Neon because they were MySQL-trained; switching to Postgres would've required learning a new dialect, and losing FX constraints in Postgres wasn't necessary (they handle validation in app code anyway). The benefit: zero downtime deployments cut their deployment risk and enabled faster iteration.
Hidden gotchas
Foreign keys are disabled by default, and the docs bury this critical fact. You only discover it when your INSERT fails with 'no referenced key' and realize the constraint never existed. Re-enabling them requires migrating your entire schema and application validation logic. Their connection pooling proxy ('Connect') adds 1-2 seconds to the first query in serverless functions because routing through their proxy is slow. Switching to native MySQL connection pooling bypasses Neon's schema safety features, creating a tradeoff between performance and safety. Billing is opaque: charged per 'read units' and 'write units,' but conversion rates are unclear from the dashboard. A single slow query can spike your bill 10x overnight without warning. They grandfather old customers on better rates while charging new signups 3x higher unit pricing—this disparity is undocumented. They killed the free tier in 2024, but many tutorials still reference it, misleading new developers. Multi-region setup requires paying for multiple deployments ($39 each), effectively doubling cost—not clearly stated upfront. Connection limits are lower than expected; you'll hit them at lower concurrency than on RDS.
Pricing breakdown
PlanetScale's Scaler plan starts at $39/mo for 10 GB storage, 1 billion row reads, and 10 million row writes. The Scaler Pro plan at $99/mo doubles these limits and adds SOC 2 compliance. They removed their free Hobby plan in April 2024. Row reads beyond the plan limit cost $1 per billion, writes cost $1.50 per million. The branching feature (Git-like schema management) is included in all paid plans. For a typical SaaS with moderate write volume, expect $39-99/mo. The main cost trap: write-heavy workloads (analytics ingestion, activity feeds) can blow past the included write quota quickly.
Deep dive: Turso
When to choose Turso
Choose Turso if you're building edge applications that need database reads at the edge with sub-10ms latency, or if you want SQLite's simplicity without managing deployment. Single-region workloads with <10GB of data fit perfectly. The free tier is generous ($0 for 8GB + 1M API requests/month), making it ideal for side projects, internal tools, and MVPs. SQLite's single-writer model works fine if you don't have concurrent writes from multiple regions. Turso is wrong if you need ACID transactions across multiple tables (SQLite has limited multi-table transaction support), you have thousands of concurrent writers, your queries involve complex joins, or you need advanced indexing like JSONB. Also wrong if you're already invested in SQL Server, Cassandra, or a different database ecosystem—SQLite is simple but completely different. Not suitable for teams expecting SQL migrations tooling on par with Postgres or those needing a dedicated database team. High-concurrency write-heavy applications will hit SQLite's single-writer bottleneck.
Real-world use case
A solo developer built an analytics dashboard for startup portfolios using Turso, deployed globally on Vercel edge functions with SQLite replicated to 5 regions. Each user's dashboard queries Turso from the nearest edge location. Load time: 40ms (10ms database, 30ms rendering). Cost: $0 (free tier). Real tradeoff: they initially tried Neon from each edge location but hit connection limits—Vercel edge functions don't support persistent connections, so each request was a new connection attempt. With Turso's HTTP API, each edge function makes a stateless request to the nearest replica with zero connection overhead. They chose Turso over Firebase because Firebase's realtime sync would've overkilled the use case; they just needed fast reads. When they added a second analytics dashboard writing to the same SQLite database, they discovered SQLite's single-writer model queued writes. On busy days, writes would queue for 100ms+, requiring them to implement a backend write queue. The lesson: edge reads are great, but writes still bottleneck at the primary.
Hidden gotchas
SQLite's single-writer model is not obvious from marketing. Multiple concurrent writes queue behind each other—if one write takes 500ms, the next write waits. This bites every developer eventually and forces you to architect write queues or batch writes in your application layer. Replication across regions is read-only on replicas—you can only write to the primary. Writes must round-trip to the primary region, negating the latency benefit for write-heavy applications. This limitation contradicts the 'edge database' marketing pitch. Their 'libSQL' dialect adds Postgres-like features incompletely and underdocumented. Trying to use features that exist in Postgres but not libSQL leads to silent failures or cryptic errors. Row limits on the free tier (8GB total) are split across all your databases—if you create 5 databases, you're splitting 8GB five ways. This isn't clear upfront. The HTTP API adds latency vs. TCP connections; if you're not on the edge, you're actually slower than direct SQLite. Complex joins become very slow at scale; SQLite was never designed for analytical queries on large datasets. You'll discover this in production, not development.
Pricing breakdown
Turso's free Starter plan includes 9 GB total storage, 500 databases, and 25 billion row reads/mo — extremely generous for SQLite-based apps. The Scaler plan at $29/mo adds 24 GB storage, 10,000 databases, and 100 billion row reads. Enterprise is custom. The per-database model means you can give each user their own SQLite database at near-zero marginal cost. Egress is free. The pricing advantage over PlanetScale is significant for read-heavy workloads. Write volume is the constraint: the Starter plan includes 50M row writes/mo, Scaler includes 200M.
Should You Use PlanetScale or Turso?
For most teams, PlanetScale is the better default: it offers non-blocking schema changes and is paid (from $39/month). Choose Turso instead if ultra-low latency at edge matters more than removed free tier in 2024. There is no universal winner — the right pick depends on your budget, team size, and whether you value non-blocking schema changes or ultra-low latency at edge more.
Choose PlanetScale if…
- •Non-blocking schema changes
- •MySQL compatibility
- •Excellent performance
Choose Turso if…
- •Ultra-low latency at edge
- •SQLite simplicity
- •Generous free tier