Deploy Budibase

Deploy and Host Budibase on Railway

Budibase is an open-source, low-code platform that empowers teams to build internal tools, forms, dashboards, and workflows rapidly. With its intuitive drag-and-drop interface and support for various data sources, Budibase enables the creation of custom applications without extensive coding knowledge.

This Railway template uses the official Budibase all-in-one Docker image and includes the supporting services required for the application, object storage, databases, background processing, and AI model integration.

About Hosting Budibase

Budibase offers flexible hosting options to suit different needs. You can self-host Budibase using Docker, Kubernetes, or cloud infrastructure, providing control over your applications and data.

This Railway template simplifies self-hosting Budibase on Railway by including the following services in a single deployment:

• Budibase application
• Budibase worker
• Redis
• CouchDB
• MinIO object storage
• PostgreSQL for LiteLLM
• LiteLLM for AI model integration

The template uses persistent storage mounted at /data, allowing application data and service files to remain available after container restarts and redeployments.

Why Deploy Budibase?

Deploying Budibase on Railway allows organizations to:

• Maintain Control: Run Budibase on your own Railway project and manage its configuration.
• Build Internal Tools: Create dashboards, administrative panels, and business applications.
• Create Forms: Develop forms for registrations, surveys, requests, and data collection.
• Manage Data: Build CRUD interfaces connected to databases and APIs.
• Automate Workflows: Create workflows with triggers, actions, and conditions.
• Integrate Services: Connect applications to databases, REST APIs, and external services.
• Use AI Models: Connect Budibase to supported AI providers through the integrated LiteLLM service.
• Simplify Deployment: Run Budibase and its supporting services through one Railway deployment.

Common Use Cases

• Internal Tools: Develop custom dashboards, management systems, and operational applications.
• Form Builders: Create dynamic forms for surveys, registrations, inspections, and requests.
• Approval Workflows: Implement approval processes for purchases, requests, and content publishing.
• Data Management: Build interfaces for creating, reading, updating, and deleting records.
• Customer Portals: Provide customers with access to selected information and workflows.
• AI-Assisted Applications: Connect Budibase applications to AI models using LiteLLM.
• Business Operations: Build applications for sales, support, inventory, finance, and administration.

Dependencies for Hosting Budibase

This template uses the official Budibase all-in-one Docker image and includes the main dependencies required for operation.

Deployment Dependencies

• Docker: Budibase is deployed using its official Docker image.
• Redis: Used by Budibase for internal processing and queues.
• CouchDB: Used for Budibase application data.
• MinIO: S3-compatible object storage for application assets.
• PostgreSQL: Used by the integrated LiteLLM service.
• LiteLLM: Provides a proxy layer for connecting to supported AI model providers.
• Railway Volume: Used for persistent data storage at /data.

No separate Redis, CouchDB, MinIO, or PostgreSQL service is required for the basic deployment because these components are included in the all-in-one container.

App Builder

Budibase features an intuitive drag-and-drop app builder that enables users to design responsive applications for desktop, tablet, and mobile devices.

With its visual interface and reusable components, you can create:

• Administrative dashboards
• Data entry interfaces
• Management systems
• Customer portals
• Internal business applications
• Custom forms and reporting screens

Automation

Budibase includes automation capabilities for creating workflows based on triggers, actions, and conditions.

Typical automation scenarios include:

• Sending notifications
• Updating database records
• Processing submitted forms
• Integrating with external APIs
• Starting approval workflows
• Triggering actions based on application events

Data Integration

Budibase supports connections to a variety of data sources, including:

• PostgreSQL
• MySQL
• Microsoft SQL Server
• MongoDB
• REST APIs
• Google Sheets
• CSV files
• Budibase internal database

These integrations allow you to build applications that read, create, update, and manage data from different systems.

LiteLLM and AI Models

This template includes LiteLLM for AI model integration.

LiteLLM runs internally on port 4000 and is available to the Budibase application through:

http://127.0.0.1:4000

The startup configuration explicitly starts LiteLLM on port 4000 to avoid conflicts with the main Budibase HTTP service, which uses port 80.

AI Provider Configuration

No AI model is registered automatically by this template.

After deployment, configure the provider credentials and model information required for your use case. The available provider configuration fields can be accessed through:

http://127.0.0.1:4000/public/providers/fields

Supported providers depend on the installed LiteLLM version and may include:

• OpenAI
• Google AI Studio
• Anthropic
• Groq
• OpenRouter
• Mistral
• DeepSeek
• Other providers supported by LiteLLM

Provider API keys and administrative secrets must remain private. Do not include them in the README, source code, screenshots, or public support discussions.

Application Ports

The deployment uses the following internal ports:

The main public service is exposed through Railway on port 80.

Persistent Storage

The template uses /data as the main persistent storage directory.

This directory is used by Budibase and the supporting services for:

• Application data
• Uploaded assets
• Internal databases
• MinIO data
• Service configuration and runtime data

Do not remove the Railway volume unless you have a backup and understand that application data and stored assets may be lost.

Getting Started

1. Click Deploy on Railway.
2. Create or select a Railway project.
3. Review the generated environment variables.
4. Confirm that a persistent volume is configured for /data.
5. Deploy the template.
6. Open the generated public domain.
7. Complete the initial Budibase setup.
8. Create your first application.
9. Configure data sources, automations, and integrations.
10. If required, configure an AI provider and model through LiteLLM.

Troubleshooting

Budibase Does Not Load

Check the Railway deployment logs and confirm that the main service is running on port 80.

AI Providers Are Not Displayed

Confirm that LiteLLM is running on port 4000 and that the provider configuration endpoint is accessible internally:

http://127.0.0.1:4000/public/providers/fields

No Models Are Listed

The template does not register an AI model by default. Configure at least one provider and model before using AI features.

Data or Assets Are Lost

Confirm that the Railway volume is mounted at:

/data

Without persistent storage, data stored inside the container may be lost after a restart or redeployment.

LiteLLM Does Not Start

Check the Railway deployment logs and confirm that LiteLLM is configured to use port 4000.

The main Budibase HTTP service uses port 80, so LiteLLM must not attempt to bind to that same port.

Documentation

• Budibase Documentation
• Getting Started with Budibase
• Budibase Data Sources
• Budibase Automation Guide
• Budibase License
• LiteLLM Documentation

License

Budibase is released under the Business Source License (BSL). Review the official Budibase license information before using the software commercially or distributing modified versions.