Querybook vs Supabase
| Tagline | Pinterest's open-source big data query notebook for collaborative SQL analytics | Open-source Firebase alternative built on PostgreSQL with realtime and auth |
| Category | Databases & Spreadsheets | Databases & Spreadsheets |
| Replaces | Retool, Google Sheets, Smartsheet | Airtable, Google Sheets, Retool |
| GitHub stars | 1.8k | 78k |
| Language | Python | TypeScript |
| License | Apache-2.0 | Apache-2.0 |
| Self-host difficulty | 4/5 Involved | 3/5 Moderate |
| Deploy options | Docker Docker Compose | Docker Docker Compose Kubernetes |
| Managed hosting | ||
| Last updated | 9 months ago | 17 days ago |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Querybook
- Primarily designed for big data query engines (Hive, Presto); poor fit for everyday OLTP databases
- No spreadsheet-style formula editing; purely a SQL notebook tool
- Requires Elasticsearch and Celery workers, adding significant infrastructure overhead
Supabase
- Self-hosted Docker Compose stack is complex: 8+ services including Kong, GoTrue, PostgREST, Realtime
- Studio table editor is less polished than Airtable UX for non-technical users
- Edge Functions are limited to Deno; no Node.js runtime in the self-hosted edition
Bottom line
Choose Supabase if you want the lower-effort setup; choose Supabase for the larger community and ecosystem. Supabase has seen more recent development. Open each guide below for deploy steps and the full feature gap.