LakeQL
Introduction
  • Overview
  • Why LakeQL
  • Key Concepts
Getting Started
  • Prerequisites
  • Quickstart
  • Environment
  • First Run
Architecture
  • System Overview
  • Data Flow
  • Request Lifecycle
Configuration
  • Config File
  • Runtime Lifecycle
  • Environment Variables
create-app
  • Usage
  • Template Structure
  • Post-Creation
Guides
  • Custom Resolvers
  • Extending the Schema
  • Mutations
  • Set Up a Trino Mutation
  • Deploying
Endpoints
  • Definition Format
  • Field Types
  • Nested Fields
  • Mutations
  • Glossary
Contributing
  • Local Development
  • Contribution Guide
  • Architecture
GitHub
LakeQL
  1. LakeQL
  2. Introduction

Introduction

What LakeQL is, the problems it solves, and how its packages fit together.

LakeQL is a universal data access layer for modern platforms. It generates a type-safe GraphQL API across your data stack. You introspect your data source, generate typed schema files, and serve them through a GraphQL server you compose from explicit building blocks. No hand-written resolvers per table.

This section sets the vocabulary the rest of the documentation builds on.

Overview

LakeQL is a universal data access layer that generates type-safe GraphQL APIs across your data stack. No hand-written resolvers.

Why LakeQL

When a managed GraphQL service is enough, and what LakeQL adds across data engines.

Key Concepts

Data sources and adapters, schema generation, the runtime, and GraphQL-to-SQL translation.

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