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Drizzle Cube

Getting Started with Drizzle Cube

Drizzle Cube is a Drizzle ORM-first semantic layer with Cube.js compatibility. It provides type-safe analytics and dashboards with SQL injection protection by leveraging Drizzle ORM as its core SQL building engine and is designed for you to embed within your own applications.

What is Drizzle Cube?

Section titled “What is Drizzle Cube?”

Drizzle Cube bridges the gap between your database and your analytics applications by providing:

  • Type-safe semantic layer - Define cubes, dimensions, and measures with full TypeScript support
  • SQL injection protection - All queries use Drizzle’s parameterized query system
  • Cube.js compatibility - Able to migrate to Cube.js when your needs become more complex or traffic scales
  • Multi-database support - Supports PostgreSQL (including Neon) and MySQL, with SQLite coming soon
  • React components - Pre-built dashboard and chart components
  • Framework agnostic - Use with any web framework via adapters

Core Concepts

Section titled “Core Concepts”

Semantic Layer

Section titled “Semantic Layer”

The semantic layer is a business-friendly abstraction over your database that sits between your raw data and your analytics applications. Instead of writing raw SQL queries throughout your application, you define cubes that encapsulate your business logic and provide:

  • Consistent metrics - Define calculations once, use everywhere
  • Security by default - Multi-tenant isolation and access control
  • Business terminology - Use familiar names instead of database columns
  • Type safety - Full TypeScript support prevents runtime errors

Cubes

Section titled “Cubes”

Cubes are the building blocks of your semantic layer. Each cube represents a business entity (like Sales, Users, Products) and references your existing Drizzle schema tables directly. Each cube contains:

  • Dimensions - Attributes you can filter and group by (like product category, customer name)
  • Measures - Numeric values you want to analyze (like total revenue, order count)
  • Security context - Automatic multi-tenant isolation
import { eq } from 'drizzle-orm'
import { defineCube } from 'drizzle-cube/server'
// Import your existing Drizzle schema
import { sales } from './schema' // Your existing Drizzle schema


export const salesCube = defineCube('Sales', {
  title: 'Sales Analytics',
  description: 'Sales data and metrics',


  // References your existing Drizzle schema tables
  sql: (ctx) => ({
    from: sales, // Your existing Drizzle table
    where: eq(sales.organisationId, ctx.securityContext.organisationId)
  }),


  dimensions: {
    productName: {
      name: 'productName',
      title: 'Product Name',
      type: 'string',
      sql: sales.productName // Direct reference to your schema column
    },
    orderDate: {
      name: 'orderDate',
      title: 'Order Date',
      type: 'time',
      sql: sales.orderDate // Direct reference to your schema column
    }
  },


  measures: {
    totalSales: {
      name: 'totalSales',
      title: 'Total Sales',
      type: 'sum',
      sql: sales.amount // Direct reference to your schema column
    },
    orderCount: {
      name: 'orderCount',
      title: 'Order Count',
      type: 'count',
      sql: sales.id // Direct reference to your schema column
    }
  }
});

Query Structure

Section titled “Query Structure”

When you query cubes, you specify what you want to analyze:

{
  "measures": ["Sales.totalSales", "Sales.orderCount"],
  "dimensions": ["Sales.productName"],
  "timeDimensions": [{
    "dimension": "Sales.orderDate",
    "granularity": "month"
  }],
  "filters": [{
    "member": "Sales.productName",
    "operator": "equals",
    "values": ["Electronics"]
  }]
}

Architecture

Section titled “Architecture”

Drizzle Cube follows a Drizzle-first architecture:

  1. Database Schema - Define your database structure using Drizzle ORM
  2. Semantic Layer - Create cubes that reference your schema
  3. Query Execution - Drizzle generates type-safe, parameterized SQL
  4. Framework Integration - Use adapters to integrate with your web framework
  5. Client Components - Render data using React components

Security Model

Section titled “Security Model”

Security is built into every layer:

  • SQL Injection Protection - Drizzle’s parameterized queries prevent SQL injection
  • Multi-tenant Security - Every cube should filter by security context
  • Type Safety - TypeScript prevents runtime errors and data inconsistencies

Next Steps

Section titled “Next Steps”

Ready to get started? Here’s what to do next:

  1. Quick Start - Build your first semantic layer
  2. Scaling Your SaaS - Learn how Drizzle Cube grows with your business
  3. Semantic Layer - Deep dive into cubes, dimensions, and measures

Community and Support

Section titled “Community and Support”