---
title: "Deploy dbt + Metabase analytics"
description: "Scheduled dbt transformations with a ready-to-use Metabase analytics layer."
category: "Analytics"
url: https://railway.com/deploy/dbt-metabase-analytics
---

# Deploy dbt + Metabase analytics

Scheduled dbt transformations with a ready-to-use Metabase analytics layer.

**[Deploy dbt + Metabase analytics on Railway](https://railway.com/template/dbt-metabase-analytics)**

- **Creator:** Anton Orel's Projects
- **Category:** Analytics
- **Total deploys:** 1

## Template content

### Metabase PostgreSQL

- **Image:** postgres:17.6-alpine@sha256:ef257d85f76e48da1c64832459b59fcaba1a4dac97bf5d7450c77753542eee94

### Metabase

- **Image:** metabase/metabase:v0.63.2@sha256:252f8c9bd56dd21158005675b55876cf9fb838e0a0e0541581af859eafe1f32e
- **Health check:** /api/health
- **Public domain:** Yes

### dbt

- **Source:** tech-progress/railway-template-dbt-metabase
- **Health check:** /health

### Warehouse PostgreSQL

- **Image:** postgres:17.6-alpine@sha256:ef257d85f76e48da1c64832459b59fcaba1a4dac97bf5d7450c77753542eee94

## Documentation

# Deploy and Host dbt + Metabase on Railway

Deploy scheduled dbt transformations, a ready-to-use Metabase dashboard, and separate PostgreSQL databases for Metabase state and warehouse data. The first boot seeds and tests an example model, connects Metabase to the warehouse, and creates a working question and dashboard.

## About Hosting dbt + Metabase

dbt turns warehouse SQL into tested, repeatable data models, while Metabase provides browser-based exploration and dashboards. This template runs dbt daily, keeps both databases private, and exposes only Metabase through Railway's public networking.

## Why Deploy dbt + Metabase on Railway

Railway supplies private service discovery, generated credentials, TLS, and persistent 5 GB database volumes. The bootstrap is idempotent, so initialized restarts preserve the administrator, warehouse connection, question, and dashboard.

## Common Use Cases

- Start a small internal analytics stack with tested SQL models and dashboards.
- Prototype a dbt project before connecting a production warehouse.
- Schedule lightweight transformations without operating a separate orchestrator.
- Give a team a private BI workspace backed by PostgreSQL.

## Dependencies for dbt + Metabase

Provision at least 2 GiB for Metabase, then replace the example dbt seed and model with your own project. Keep one dbt replica because every replica runs the same scheduled transformation.

### Deployment Dependencies

- dbt Core `1.12.0` with dbt-postgres `1.11.0`
- Metabase `0.63.2`
- Two PostgreSQL `17.6` services with persistent volumes


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