Databasus PostgreSQL Backup Tool Gains Anthropic Open Source Support

Anthropic's Recognition of Databasus
Anthropic has recognized Databasus through their Claude for Open Source program, which gives maintainers of qualifying open source projects free access to Claude Max. The program has high requirements: projects need 5,000+ GitHub stars or 1M+ monthly NPM downloads, active maintenance, and real community adoption. They accept up to 10,000 maintainers total and review each application individually.
What is Databasus?
Databasus is an open source self-hosted tool for database backups. It started as a small internal tool called Postgresus for backing up PostgreSQL databases a couple of years ago. Over time the project added support for MySQL, MariaDB and MongoDB (though PostgreSQL is still the main focus), and was renamed to Databasus in the end of 2025.
Key technical details:
- Runs as a single Docker container
- All data stays on your infrastructure
- Apache 2.0 license
- 5,800+ stars on GitHub
- 250k+ Docker pulls
- Became the most starred PostgreSQL backup tool on GitHub in 2025, passing WAL-G, pgBackRest and Barman
Main Features
- Scheduled backups (hourly, daily, weekly, monthly or custom cron)
- 70+ storage destinations: local disk, S3, Cloudflare R2, Google Drive, Dropbox, SFTP, NAS and more via Rclone
- AES-256-GCM encryption with unique keys per backup file
- Retention policies: time period, count, size limit, or GFS (Grandfather-Father-Son) for enterprise compliance
- Database health monitoring with configurable failure thresholds
- Team features: workspaces, RBAC (viewer/member/admin/owner), audit logs
- Notifications: Slack, Discord, Telegram, MS Teams, Email, webhooks
- Works with cloud-managed databases like AWS RDS, Google Cloud SQL and Azure
- Full backup portability: you can decrypt and restore backups using only secret.key and standard tools, without Databasus itself
AI Usage Policy
The project maintains transparency about AI usage with a dedicated AI disclaimer in the README. They use Claude models exclusively for development because other models are "less reliable and more noisy."
AI is used for:
- Verification of code quality and searching for vulnerabilities
- Cleaning up and improving documentation, comments and code
- Assistance during development
- Double-checking PRs and commits after human review
AI is NOT used for:
- Writing entire code
- "Vibe code" approach
- Code without line-by-line verification by a human
- Code without tests
The project has solid test coverage (unit and integration), CI/CD pipeline with tests and linting, and verification by experienced developers. Vibe coded PRs are rejected by default, and they've denied PRs because of "AI slop" (see GitHub issue #145).
The developer's philosophy: "Use AI as a tool, but don't rely on it too much. At the end of the day, you are responsible for what you release to the public. People trust your project with their data, and that's not something you hand off to a language model."
📖 Read the full source: r/ClaudeAI
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