Fly.io vs PlanetScale

Detailed side-by-side comparison

Fly.io

Fly.io

Free

Fly.io is a global application platform that deploys full-stack applications as lightweight microVMs distributed across 30+ regions worldwide. It excels at running applications close to users for minimal latency, offering automatic scaling, built-in load balancing, and support for Docker containers with a simple CLI-driven deployment workflow.

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PlanetScale

PlanetScale

Free

PlanetScale is a serverless MySQL database platform built on Vitess that revolutionizes database development with Git-like branching workflows. It enables horizontal scaling without code changes and provides non-blocking schema migrations, making database changes safe and collaborative while eliminating downtime during deployments.

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Feature Comparison

FeatureFly.ioPlanetScale
Primary Use CaseApplication hosting and compute platform for deploying full-stack applications globallyManaged database platform specifically for MySQL workloads with advanced developer workflows
Global DistributionDeploys applications across 30+ edge regions with Anycast networking for automatic routing to nearest instanceDatabase can be deployed in multiple regions with read replicas, though primarily focused on single-region writes
Scaling ApproachVertical and horizontal scaling of application instances with automatic load balancing across regionsHorizontal database scaling through Vitess sharding without requiring application code modifications
Developer WorkflowCLI-based deployment of Docker containers with zero-downtime rolling deployments and health checksGit-like branching for databases with deploy requests, enabling safe schema changes through review processes
Schema Changes & MigrationsApplication-level migrations managed by your framework, requires coordination with deploymentsNon-blocking online DDL with zero-downtime schema changes and built-in deploy request workflow
Built-in Database SupportNative support for PostgreSQL and Redis, can run other databases as containersMySQL-compatible only (built on Vitess), with limitations like no foreign key constraint support

Pricing Comparison

Both platforms offer generous free tiers starting at $0/month, making them accessible for small projects and development. Fly.io uses pay-per-use pricing based on compute resources and bandwidth which can become unpredictable, while PlanetScale's pricing scales with database reads, writes, and storage, potentially becoming more expensive than traditional managed databases at higher scales.

Verdict

Choose Fly.io if...

Choose Fly.io if you need to deploy and run full-stack applications with minimal latency for globally distributed users, want flexibility to run any containerized application, or need a complete compute platform beyond just database hosting.

Choose PlanetScale if...

Choose PlanetScale if you need a MySQL database with advanced developer workflows, want to eliminate downtime during schema changes, require horizontal scaling without application refactoring, or prioritize collaborative database development with branching and review processes.

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Pros & Cons

Fly.io

Pros

  • + Extremely low latency with edge deployment capabilities
  • + Pay-per-use pricing model with generous free tier
  • + Simple deployment workflow with flyctl CLI
  • + Excellent performance for geographically distributed applications

Cons

  • - Steeper learning curve compared to traditional PaaS platforms
  • - Pricing can become unpredictable with variable traffic
  • - Smaller ecosystem and community compared to AWS or Heroku

PlanetScale

Pros

  • + Eliminates downtime during schema changes with online DDL
  • + Git-like branching workflow makes database development safer and more collaborative
  • + Scales horizontally without application code changes
  • + Generous free tier suitable for hobby projects and small applications

Cons

  • - Limited to MySQL compatibility only, no PostgreSQL or other database support
  • - Foreign key constraints are not supported due to Vitess architecture
  • - Can be more expensive than traditional managed databases at higher scales