Backup tool for PostgreSQL, MySQL and MongoDB

Databasus is a free, open source and self-hosted tool to backup databases (with focus on PostgreSQL). Make backups with different storages (S3, Google Drive, FTP, etc.) and notifications about progress (Slack, Discord, Telegram, etc.). Previously known as Postgresus (see migration guide).

Features • Installation • Usage • License • Contributing

🌐 Databasus website

• PostgreSQL: 12, 13, 14, 15, 16, 17 and 18
• MySQL: 5.7, 8 and 9
• MariaDB: 10 and 11
• MongoDB: 4, 5, 6, 7 and 8

• Flexible scheduling: hourly, daily, weekly, monthly or cron
• Precise timing: run backups at specific times (e.g., 4 AM during low traffic)
• Smart compression: 4-8x space savings with balanced compression (~20% overhead)

• Time period: Keep backups for a fixed duration (e.g., 7 days, 3 months, 1 year)
• Count: Keep a fixed number of the most recent backups (e.g., last 30)
• GFS (Grandfather-Father-Son): Layered retention — keep hourly, daily, weekly, monthly and yearly backups independently for fine-grained long-term history (enterprises requirement)
• Size limits: Set per-backup and total storage size caps to control storage usage

• Local storage: Keep backups on your VPS/server
• Cloud storage: S3, Cloudflare R2, Google Drive, NAS, Dropbox, SFTP, Rclone and more
• Secure: All data stays under your control

• Multiple channels: Email, Telegram, Slack, Discord, webhooks
• Real-time updates: Success and failure notifications
• Team integration: Perfect for DevOps workflows

• AES-256-GCM encryption: Enterprise-grade protection for backup files
• Zero-trust storage: Backups are encrypted and remain useless to attackers, so you can safely store them in shared storage like S3, Azure Blob Storage, etc.
• Encryption for secrets: Any sensitive data is encrypted and never exposed, even in logs or error messages
• Read-only user: Databasus uses a read-only user by default for backups and never stores anything that can modify your data

It is also important for Databasus that you are able to decrypt and restore backups from storages (local, S3, etc.) without Databasus itself. To do so, read our guide on how to recover directly from storage. We avoid "vendor lock-in" even to open source tool!

• Workspaces: Group databases, notifiers and storages for different projects or teams
• Access management: Control who can view or manage specific databases with role-based permissions
• Audit logs: Track all system activities and changes made by users
• User roles: Assign viewer, member, admin or owner roles within workspaces

• Designer-polished UI: Clean, intuitive interface crafted with attention to detail
• Dark & light themes: Choose the look that suits your workflow
• Mobile adaptive: Check your backups from anywhere on any device

Databasus works seamlessly with both self-hosted PostgreSQL and cloud-managed databases:

• Cloud support: AWS RDS, Google Cloud SQL, Azure Database for PostgreSQL
• Self-hosted: Any PostgreSQL instance you manage yourself
• Why no PITR support?: Cloud providers already offer native PITR, and external PITR backups cannot be restored to managed cloud databases — making them impractical for cloud-hosted PostgreSQL
• Practical granularity: Hourly and daily backups are sufficient for 99% of projects without the operational complexity of WAL archiving

• Docker-based: Easy deployment and management
• Privacy-first: All your data stays on your infrastructure
• Open source: Apache 2.0 licensed, inspect every line of code

You have four ways to install Databasus:

• Automated script (recommended)
• Simple Docker run
• Docker Compose setup
• Kubernetes with Helm

You have four ways to install Databasus: automated script (recommended), simple Docker run, or Docker Compose setup.

The installation script will:

• ✅ Install Docker with Docker Compose (if not already installed)
• ✅ Set up Databasus
• ✅ Configure automatic startup on system reboot

sudo apt-get install -y curl && \
sudo curl -sSL https://raw.githubusercontent.com/databasus/databasus/refs/heads/main/install-databasus.sh \
| sudo bash

The easiest way to run Databasus:

docker run -d \
  --name databasus \
  -p 4005:4005 \
  -v ./databasus-data:/databasus-data \
  --restart unless-stopped \
  databasus/databasus:latest

This single command will:

• ✅ Start Databasus
• ✅ Store all data in ./databasus-data directory
• ✅ Automatically restart on system reboot

Create a docker-compose.yml file with the following configuration:

services:
  databasus:
    container_name: databasus
    image: databasus/databasus:latest
    ports:
      - "4005:4005"
    volumes:
      - ./databasus-data:/databasus-data
    restart: unless-stopped

Then run:

docker compose up -d

For Kubernetes deployments, install directly from the OCI registry.

With ClusterIP + port-forward (development/testing):

helm install databasus oci://ghcr.io/databasus/charts/databasus \
  -n databasus --create-namespace

kubectl port-forward svc/databasus-service 4005:4005 -n databasus
# Access at http://localhost:4005

With LoadBalancer (cloud environments):

helm install databasus oci://ghcr.io/databasus/charts/databasus \
  -n databasus --create-namespace \
  --set service.type=LoadBalancer

kubectl get svc databasus-service -n databasus
# Access at http://<EXTERNAL-IP>:4005

With Ingress (domain-based access):

helm install databasus oci://ghcr.io/databasus/charts/databasus \
  -n databasus --create-namespace \
  --set ingress.enabled=true \
  --set ingress.hosts[0].host=backup.example.com

For more options (NodePort, TLS, HTTPRoute for Gateway API), see the Helm chart README.

1. Access the dashboard: Navigate to http://localhost:4005
2. Add your first database for backup: Click "New Database" and follow the setup wizard
3. Configure schedule: Choose from hourly, daily, weekly, monthly or cron intervals
4. Set database connection: Enter your database credentials and connection details
5. Choose storage: Select where to store your backups (local, S3, Google Drive, etc.)
6. Configure retention policy: Choose time period, count or GFS to control how long backups are kept
7. Add notifications (optional): Configure email, Telegram, Slack, or webhook notifications
8. Save and start: Databasus will validate settings and begin the backup schedule

If you need to reset the password, you can use the built-in password reset command:

docker exec -it databasus ./main --new-password="YourNewSecurePassword123" --email="admin"

Replace admin with the actual email address of the user whose password you want to reset.

After installation, it is also recommended to backup your Databasus itself or, at least, to copy secret key used for encryption (30 seconds is needed). So you are able to restore from your encrypted backups if you lose access to the server with Databasus or it is corrupted.

This project is licensed under the Apache 2.0 License - see the LICENSE file for details

Contributions are welcome! Read the contributing guide for more details, priorities and rules. If you want to contribute but don't know where to start, message me on Telegram @rostislav_dugin

Also you can join our large community of developers, DBAs and DevOps engineers on Telegram @databasus_community.

There have been questions about AI usage in project development in issues and discussions. As the project focuses on security, reliability and production usage, it's important to explain how AI is used in the development process.

AI is used as a helper 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 (both unit and integration tests)
• CI/CD pipeline automation with tests and linting to ensure code quality
• verification by experienced developers with experience in large and secure projects

So AI is just an assistant and a tool for developers to increase productivity and ensure code quality. The work is done by developers.

Moreover, it's important to note that we do not differentiate between bad human code and AI vibe code. There are strict requirements for any code to be merged to keep the codebase maintainable.

Even if code is written manually by a human, it's not guaranteed to be merged. Vibe code is not allowed at all and all such PRs are rejected by default (see contributing guide).

We also draw attention to fast issue resolution and security vulnerability reporting.