# Redash — Open Source Data Visualization & Dashboard Tool

> Redash connects to any data source, lets you query with SQL, visualize results, and build shareable dashboards. The SQL-first open-source BI tool for data teams.

## Install

Save in your project root:

## Quick Use

```bash
git clone https://github.com/getredash/setup.git redash-setup
cd redash-setup
docker compose up -d
```

Open `http://localhost:5000` — create your admin account and connect your first data source.

## Intro

**Redash** is an open-source data visualization and dashboarding tool designed for data analysts and engineers. It connects to virtually any data source, provides a powerful SQL editor with autocomplete, and lets you build interactive dashboards that can be shared across your organization.

With 28.3K+ GitHub stars and BSD-2-Clause license, Redash is the go-to SQL-first BI tool for teams that prefer writing queries over drag-and-drop builders.

## What Redash Does

- **SQL Editor**: Full-featured SQL editor with schema browser, autocomplete, and query history
- **50+ Data Sources**: PostgreSQL, MySQL, BigQuery, Snowflake, Redshift, ClickHouse, MongoDB, APIs, and more
- **Visualizations**: Charts, tables, maps, pivot tables, word clouds, and more from query results
- **Dashboards**: Compose visualizations into interactive dashboards with filters and parameters
- **Alerts**: Automated alerts when query results match conditions (email, Slack, webhook)
- **Scheduled Queries**: Auto-refresh queries on a schedule (hourly, daily, weekly)
- **Sharing**: Share queries and dashboards with team via links or embedding
- **API**: Full REST API for programmatic access to queries and results
- **Parameters**: Parameterized queries for dynamic, interactive dashboards

## Architecture

```
┌──────────────┐     ┌──────────────┐     ┌──────────────┐
│  Browser     │────▶│  Redash      │────▶│  Your Data   │
│  Dashboard   │     │  Server      │     │  PostgreSQL  │
└──────────────┘     │  (Python/    │     │  MySQL       │
                     │   Flask)     │     │  BigQuery    │
                     └──────┬───────┘     │  Snowflake   │
                            │             │  ClickHouse  │
                     ┌──────┴───────┐     │  50+ more    │
                     │  Redis +     │     └──────────────┘
                     │  PostgreSQL  │
                     │  (Metadata)  │
                     └──────────────┘
```

## Self-Hosting

### Docker Compose

```yaml
services:
  redash:
    image: redash/redash:latest
    command: server
    ports:
      - "5000:5000"
    environment:
      REDASH_DATABASE_URL: postgresql://redash:redash@postgres/redash
      REDASH_REDIS_URL: redis://redis:6379/0
      REDASH_SECRET_KEY: your-secret-key
    depends_on:
      - postgres
      - redis

  worker:
    image: redash/redash:latest
    command: worker
    environment:
      REDASH_DATABASE_URL: postgresql://redash:redash@postgres/redash
      REDASH_REDIS_URL: redis://redis:6379/0

  scheduler:
    image: redash/redash:latest
    command: scheduler
    environment:
      REDASH_DATABASE_URL: postgresql://redash:redash@postgres/redash
      REDASH_REDIS_URL: redis://redis:6379/0

  postgres:
    image: postgres:16-alpine
    environment:
      POSTGRES_USER: redash
      POSTGRES_PASSWORD: redash
      POSTGRES_DB: redash
    volumes:
      - pg-data:/var/lib/postgresql/data

  redis:
    image: redis:7-alpine

volumes:
  pg-data:
```

## Key Features

### Parameterized Queries

```sql
-- Parameters appear as {{param_name}} in queries
SELECT
  date_trunc('{{period}}', created_at) as period,
  COUNT(*) as orders,
  SUM(total) as revenue
FROM orders
WHERE created_at BETWEEN '{{start_date}}' AND '{{end_date}}'
  AND status = '{{status}}'
GROUP BY 1
ORDER BY 1

-- Parameters become dropdown/date picker controls in the dashboard
-- period: day, week, month (dropdown)
-- start_date, end_date: date pickers
-- status: completed, pending, cancelled (dropdown from query)
```

### Visualization Types

| Type | Best For |
|------|----------|
| Line/Area Chart | Time series trends |
| Bar Chart | Category comparisons |
| Pie/Donut | Proportions |
| Scatter | Correlations |
| Pivot Table | Multi-dimensional analysis |
| Map (Choropleth) | Geographic data |
| Counter | Single KPI number |
| Funnel | Conversion analysis |
| Word Cloud | Text frequency |
| Cohort | Retention analysis |

### Scheduled Queries & Alerts

```
Query: "Daily Active Users"
Schedule: Every day at 8am
Alert: When result < 1000
  → Send to Slack #metrics
  → Email to team@company.com
```

### Query Snippets

```sql
-- Save reusable SQL snippets
-- Snippet: "date_filter"
WHERE created_at BETWEEN '{{start_date}}' AND '{{end_date}}'

-- Snippet: "user_join"
LEFT JOIN users u ON u.id = t.user_id

-- Use with trigger keyword in SQL editor
```

## Redash vs Alternatives

| Feature | Redash | Metabase | Grafana | Superset |
|---------|--------|----------|---------|----------|
| Query approach | SQL-first | Visual + SQL | PromQL + SQL | SQL + visual |
| Data sources | 50+ | 20+ | 100+ | 30+ |
| Ease of use | Medium (SQL) | Easy (no-code) | Medium | Medium |
| Best for | Data/SQL teams | Business users | DevOps/SRE | Data teams |
| Alerts | Yes | Yes | Yes | Yes |
| Embedding | Basic | Advanced | Yes | Yes |
| Community | Large | Very large | Very large | Large |

## 常见问题

**Q: Redash 和 Metabase 怎么选？**
A: 如果你的团队习惯写 SQL，Redash 更自然。如果团队中有非技术人员需要自主探索数据，Metabase 的可视化查询构建器更友好。两者都可以免费自托管。

**Q: Redash 还在积极维护吗？**
A: Redash 被 Databricks 收购后，官方开发节奏放缓。但社区仍在活跃维护（合并 PR 和修复 bug）。对于新项目，也可以考虑 Metabase 或 Apache Superset。

**Q: 可以可视化 API 数据吗？**
A: 可以。Redash 支持 JSON API 和 Python 脚本作为数据源。你可以写 Python 代码调用任何 API 并返回结果用于可视化。

## 来源与致谢

- GitHub: [getredash/redash](https://github.com/getredash/redash) — 28.3K+ ⭐ | BSD-2-Clause
- 官网: [redash.io](https://redash.io)

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Source: https://tokrepo.com/en/workflows/a20e0e3e-34d0-11f1-9bc6-00163e2b0d79
Author: AI Open Source