LakeQL - Introduction - Overview

What is LakeQL? #

LakeQL is a toolkit that automatically generates a type-safe GraphQL API on top of your Trino data lakehouse. It introspects your Trino schemas, generates TypeScript interfaces and query schemas, and serves them through a production-ready GraphQL API with built-in pagination, filtering, and sorting.

The Problem #

Manually writing GraphQL resolvers for data lakehouse tables is repetitive and error-prone. Every time a table changes, you update interfaces, resolvers, and type definitions by hand. Schema drift, missing fields, and inconsistent filtering logic creep in fast — especially when your lakehouse has dozens of tables across multiple schemas.

The Solution #

LakeQL flips the workflow. Instead of writing resolvers manually, you introspect your Trino catalog and generate everything:

TypeScript interfaces from column metadata
Pothos query schemas with filtering, sorting, and pagination baked in
JSON schemas for response transformation
A config registry that ties it all together at runtime

The generated code is fully typed end-to-end, from GraphQL input to SQL output.

Pull a schema from Trino and generate all artifacts:

npx lakeql-cli pull --catalog hive --schema sales

Key Benefits #

Type safety — Generated TypeScript interfaces ensure compile-time correctness from GraphQL layer to SQL queries
Automatic schema generation — Run one CLI command to generate resolvers, types, and configs for entire schemas
Pothos-based schema builder — Leverage the Pothos GraphQL schema builder for type-safe, declarative schema construction
Built-in pagination — Connection-based pagination with pageInfo metadata out of the box
Flexible filtering — AND/OR combinable filters with operators like eq , neq , like , in , gt , lt , and more
Sorting — Multi-field sorting with ASC/DESC direction
Permission model — Read/write permission checks per table with support for user-level and system-user flows
Kysely SQL generation — SQL queries are built with Kysely, giving you type-safe query construction without raw strings

How It Works #

Introspect — The CLI connects to Trino and discovers table structures
Generate — TypeScript files are written with interfaces, query schemas, and configs
Serve — The API server loads generated schemas and exposes a GraphQL endpoint
Query — Clients send GraphQL queries that are translated into optimized Trino SQL

TypeScript interfaces from column metadata
Pothos query schemas with filtering, sorting, and pagination baked in
JSON schemas for response transformation
A config registry that ties it all together at runtime

The generated code is fully typed end-to-end, from GraphQL input to SQL output.

Pull a schema from Trino and generate all artifacts:

npx lakeql-cli pull --catalog hive --schema sales

Key Benefits #

Type safety — Generated TypeScript interfaces ensure compile-time correctness from GraphQL layer to SQL queries
Automatic schema generation — Run one CLI command to generate resolvers, types, and configs for entire schemas
Pothos-based schema builder — Leverage the Pothos GraphQL schema builder for type-safe, declarative schema construction
Built-in pagination — Connection-based pagination with pageInfo metadata out of the box
Flexible filtering — AND/OR combinable filters with operators like eq , neq , like , in , gt , lt , and more
Sorting — Multi-field sorting with ASC/DESC direction
Permission model — Read/write permission checks per table with support for user-level and system-user flows
Kysely SQL generation — SQL queries are built with Kysely, giving you type-safe query construction without raw strings

How It Works #

Introspect — The CLI connects to Trino and discovers table structures
Generate — TypeScript files are written with interfaces, query schemas, and configs
Serve — The API server loads generated schemas and exposes a GraphQL endpoint
Query — Clients send GraphQL queries that are translated into optimized Trino SQL