MongoDB Atlas vs PlanetScale

At a Glance

MongoDB Atlas

PlanetScale

MongoDB Atlas

PlanetScale

MongoDB Atlas

Pros

The flexible document model means you can iterate on your data shape in early product development without migrations+132
Atlas Search gives you full-text search with relevance ranking built directly into your database without a separate service+118
The aggregation pipeline is incredibly powerful once you learn it — complex transformations that would require joins in SQL are often one pipeline stage+104
Global clusters with regional reads and writes let you build truly multi-region apps without managing replication yourself+89

Cons

Schema-less sounds great until you have inconsistent data across millions of documents and no enforcement to help you find the problem

Database

MongoDB Atlas vs Supabase

Database

Supabase vs Firebase vs PlanetScale

Database

PlanetScale vs Neon

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PlanetScale

Pros

Branching model for database schema changes means you never run a raw ALTER TABLE in production again — a game changer for team workflows+183
Zero-downtime schema migrations are solved by default — no more 3am maintenance windows for adding a column+162
Vitess under the hood means it handles enormous write throughput that would kill a vanilla Postgres setup+147
The query insights dashboard identifies slow queries with execution plans before they become production incidents+109

Cons

They killed the free tier in 2024 and the cheapest plan is $39/mo — hard to justify for early-stage projects that might not survive+198
It's MySQL not Postgres, which cuts you off from a huge ecosystem of Postgres-native tools, extensions, and hiring pool+176
Foreign key constraints aren't supported because of the sharding model — you have to enforce referential integrity in application code+152
Prisma support works but you lose some ORM features due to the missing FK support, and you'll hit confusing errors if you're not aware+91