Grist
Neon
| Feature | Grist | Neon |
|---|---|---|
| Pricing | Free / from $10/mo | Free / from $19/mo |
| Free Plan | ✓ Yes | ✓ Yes |
| Rating | 4.3 / 5 | 4.5 / 5 |
| Best For | developers, data-teams, non-profits, open-source-advocates | startups, jamstack-developers, serverless-apps, side-projects |
| Founded | 2019 | 2021 |
| Relational Data | ✓ | ✗ |
| Python Formulas | ✓ | ✗ |
| Custom Widgets | ✓ | ✗ |
| Access Rules | ✓ | ✗ |
| Incremental Imports | ✓ | ✗ |
| Api | ✓ | ✗ |
| Serverless Postgres | ✗ | ✓ |
| Branching | ✗ | ✓ |
| Autoscaling | ✗ | ✓ |
| Scale To Zero | ✗ | ✓ |
| Point In Time Recovery | ✗ | ✓ |
| Connection Pooling | ✗ | ✓ |
| Logical Replication | ✗ | ✓ |
✓ Grist Pros
- Fully open-source (Apache 2.0)
- Python formulas instead of spreadsheet formulas
- Self-hostable
- Strong access control and permissions
✗ Grist Cons
- Fewer integrations than Airtable
- Smaller template library
- Less intuitive for non-technical users
✓ Neon Pros
- Generous free tier with autoscaling
- Database branching for development workflows
- Scale-to-zero reduces costs for low-traffic apps
- Full PostgreSQL compatibility
- Instant database provisioning
✗ Neon Cons
- Relatively new platform (less battle-tested)
- Cold starts when scaling from zero
- Some PostgreSQL extensions not yet supported
The Verdict
Grist is built for developers and data teams, with a focus on relational-data and python-formulas. Neon targets startups and jamstack developers and leads with serverless-postgres and branching.
On pricing, Grist is the clear winner for budget-conscious users — starting at $10/mo compared to $19/mo for Neon. That $9/mo difference adds up quickly for growing teams.
Both offer free plans, so you can test each with your real workflow before committing to a subscription.
Feature-wise, Neon offers broader built-in capabilities (7 features vs 6), while Grist takes a more focused approach — which can mean a simpler, faster onboarding experience.
This is a genuinely close comparison. If you can, sign up for both free trials (where available) and run a one-week test with your actual team tasks before deciding.