Neon vs Fauna
A detailed comparison to help you choose between Neon and Fauna.
Quick Verdict
4.6/5
Neon
305 reviews
3.8/5
Fauna
339 reviews
Neon is rated higher (4.6 vs 3.8). Neon is serverless PostgreSQL with database branching, scale-to-zero, and connection pooling. Scales to zero when not in use — no idle charges. 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.
Neon Serverless Postgres with branching and scale-to-zero | Fauna Serverless document database with ACID transactions | |
|---|---|---|
| Overview | ||
| Rating | 4.6 (305 reviews)✓ | 3.8 (339 reviews) |
| Pricing model | freemium | freemium |
| Starting price | Free tier available | Free tier available |
| Best for | Developers using Next.js or serverless frameworks who want Postgres with branching at zero idle cost | Jamstack developers who need a serverless database with GraphQL API and automatic global replication |
| Specifications (entry plan) | ||
| CPU cores | 0 vCPU | — |
| RAM | 0 GB | — |
| Storage | 0 GB | — |
| Bandwidth | 0 TB/mo | — |
| SLA uptime | 99.9% | — |
| Data-center count | 8 | — |
| Features | ||
| IPv6 | ||
| DDoS protection | ||
| Automated backups | ✓ | |
| Snapshots | ||
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ✓ | |
| Free tier | ✓ | |
| Data-center locations | ||
| Regions | United StatesEuropean Union | — |
| Tags | ||
| Tags | free tiermanaged optionbackups includedeu datacenterus datacenterapi accessopen source | free tierapi access |
| Visit Neon → | Visit Fauna → | |
Neon
Pros
- + Scale-to-zero — no charges for idle databases
- + Database branching for preview environments
- + Generous free tier — 10 projects
Cons
- - Cold start latency when scaled to zero
- - Less mature than managed RDS for mission-critical
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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