Directus vs Fauna
A detailed comparison to help you choose between Directus and Fauna.
Quick Verdict
3.5/5
Directus
368 reviews
3.8/5
Fauna
339 reviews
Fauna is rated higher (3.8 vs 3.5). Directus wraps any SQL database with a no-code data studio, REST and GraphQL API, and file management. Open source and self-hostable. Directus Cloud is managed hosting. Fauna is a serverless document database with ACID transactions, native GraphQL API, and global replication. No servers to manage. Unique multi-tenancy model. Ideal for Jamstack and serverless apps.
Directus Open-source headless CMS and database API | Fauna Serverless document database with ACID transactions | |
|---|---|---|
| Overview | ||
| Rating | 3.5 (368 reviews) | 3.8 (339 reviews)✓ |
| Pricing model | freemium | freemium |
| Starting price | Free tier available | Free tier available |
| Best for | Development teams building headless applications who need API-first database management with self-hosting flexibility and existing SQL infrastructure. | Jamstack developers who need a serverless database with GraphQL API and automatic global replication |
| Tags | ||
| Tags | free tieropen sourceself hostableapi access | free tierapi access |
| Visit Directus → | Visit Fauna → | |
Directus
Pros
- + Generate REST and GraphQL APIs directly from existing databases without coding
- + Self-host on your infrastructure or use managed cloud for complete data control
- + Support multiple SQL databases prevents vendor lock-in
- + Real-time updates via WebSockets for live collaborative features
- + Granular role-based permissions and audit logging included
Cons
- - Steep learning curve for complex permission hierarchies and workflow automation
- - Self-hosted deployments require DevOps expertise for production stability
- - Community and ecosystem smaller than established CMS platforms like Strapi
Fauna
Pros
- + Serverless — no scaling needed
- + GraphQL API native
- + ACID transactions across global regions
Cons
- - Proprietary FQL query language
- - Pricing can surprise at scale
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