QueryLeaf

SQL to MongoDB query translator for NodeJS

Overview

QueryLeaf is a library that translates SQL queries into MongoDB commands. It parses SQL using node-sql-parser, transforms it into an abstract command set, and then executes those commands against the MongoDB Node.js driver.

Features

• Parse SQL statements into an abstract syntax tree using node-sql-parser
• Compile SQL AST into MongoDB commands
• Execute MongoDB commands using the official driver
• Support for basic SQL operations:
  • SELECT
  • INSERT
  • UPDATE
  • DELETE
• Advanced querying features:
  • Nested field access (e.g., address.zip)
  • Array element access (e.g., items[0].name)
  • GROUP BY with aggregation functions (COUNT, SUM, AVG, MIN, MAX)
  • JOINs between collections
• Multiple interfaces:
  • Library for direct integration in your code
  • CLI for command-line SQL queries
  • Web Server for REST API access
  • PostgreSQL Wire Protocol Server for connecting with standard PostgreSQL clients

SQL to MongoDB Translation Examples

QueryLeaf translates SQL queries into MongoDB commands. Here are some examples of the translation:

Basic SELECT with WHERE

SQL:

SELECT name, email FROM users WHERE age > 21

MongoDB:

db.collection('users').find(
  { age: { $gt: 21 } }, 
  { name: 1, email: 1 }
)

Nested Field Access

SQL:

SELECT name, address.city, address.zip FROM users WHERE address.city = 'New York'

MongoDB:

db.collection('users').find(
  { 'address.city': 'New York' }, 
  { name: 1, 'address.city': 1, 'address.zip': 1 }
)

Array Element Access

SQL:

SELECT _id, items[0].name, items[0].price FROM orders WHERE items[0].price > 1000

MongoDB:

db.collection('orders').find(
  { 'items.0.price': { $gt: 1000 } }, 
  { _id: 1, 'items.0.name': 1, 'items.0.price': 1 }
)

GROUP BY with Aggregation

SQL:

SELECT status, COUNT(*) as count, SUM(total) as total_amount FROM orders GROUP BY status

MongoDB:

db.collection('orders').aggregate([
  { 
    $group: {
      _id: "$status",
      status: { $first: "$status" },
      count: { $sum: 1 },
      total_amount: { $sum: "$total" }
    }
  }
])

JOIN Between Collections

SQL:

SELECT u.name, o._id as order_id, o.total FROM users u JOIN orders o ON u._id = o.userId

MongoDB:

db.collection('users').aggregate([
  {
    $lookup: {
      from: "orders",
      localField: "_id",
      foreignField: "userId",
      as: "orders"
    }
  },
  { $unwind: { path: "$orders", preserveNullAndEmptyArrays: true } },
  {
    $project: {
      name: 1,
      order_id: "$orders._id",
      total: "$orders.total"
    }
  }
])

Installation

npm install @queryleaf/lib

Usage

QueryLeaf takes your existing MongoDB client. It never creates or manages MongoDB connections on its own.

import { QueryLeaf } from '@queryleaf/lib';
import { MongoClient } from 'mongodb';

// Your existing MongoDB client
const mongoClient = new MongoClient('mongodb://localhost:27017');
await mongoClient.connect();

// Create QueryLeaf with your MongoDB client
const queryLeaf = new QueryLeaf(mongoClient, 'mydatabase');

// Execute SQL queries against your MongoDB database
const results = await queryLeaf.execute('SELECT * FROM users WHERE age > 21');
console.log(results);

// When you're done, close your MongoDB client
// (QueryLeaf never manages MongoDB connections)
await mongoClient.close();

Testing with DummyQueryLeaf

For testing or debugging without a real database, use DummyQueryLeaf:

import { DummyQueryLeaf } from '@queryleaf/lib';

// Create a DummyQueryLeaf instance for testing
const queryLeaf = new DummyQueryLeaf('mydatabase');

// Operations will be logged to console but not executed
await queryLeaf.execute('SELECT * FROM users WHERE age > 21');
// [DUMMY MongoDB] FIND in mydatabase.users with filter: { "age": { "$gt": 21 } }
// [DUMMY MongoDB] Executing find on users

Examples

The repository includes several examples:

• src/examples/existing-client-demo.ts - Shows how to use QueryLeaf in a real application
• src/examples/basic-usage.ts - Demonstrates basic usage with an existing MongoDB client
• src/examples/dummy-client-demo.ts - Shows how to use DummyQueryLeaf for testing

You can run the examples with:

# Main application example
ts-node src/examples/existing-client-demo.ts

# Basic usage example
npm run example

# Dummy client example
ts-node src/examples/dummy-client-demo.ts

SQL Query Examples

Here are some practical SQL queries you can use with QueryLeaf:

Working with Nested Fields

-- Query users by nested address field
SELECT name, email, address.city FROM users WHERE address.zip = '10001'

-- Insert with nested document structure
INSERT INTO users (name, age, email, address) VALUES 
('Jane Smith', 28, '[email protected]', {
  "street": "456 Park Ave",
  "city": "Chicago",
  "state": "IL",
  "zip": "60601"
})

-- Update a nested field
UPDATE users SET address.city = 'San Francisco', address.state = 'CA' WHERE _id = '123'

Working with Array Fields

-- Query by array element property
SELECT userId, total FROM orders WHERE items[0].name = 'Laptop'

-- Filter by array element condition
SELECT * FROM orders WHERE items[1].price < 50

-- Insert document with array field
INSERT INTO orders (userId, items, status) VALUES
('user123', [
  { "id": "prod1", "name": "Monitor", "price": 300 },
  { "id": "prod2", "name": "Keyboard", "price": 75 }
], 'pending')

Advanced Queries

-- Using GROUP BY with aggregation functions
SELECT category, COUNT(*) as count, AVG(price) as avg_price FROM products GROUP BY category

-- JOIN between users and orders
SELECT u.name, o.total, o.status FROM users u JOIN orders o ON u._id = o.userId WHERE o.total > 100

Check out the examples folder for more complete examples, including how to set up the QueryLeaf instance and execute these queries.

This library demonstrates:

• Basic SELECT queries
• Filtering with WHERE clauses
• Sorting with ORDER BY
• INSERT, UPDATE, and DELETE operations
• Accessing nested fields with dot notation
• Accessing array elements with indexing
• Aggregation with GROUP BY and aggregation functions
• Joining collections with JOIN syntax

Architecture

QueryLeaf follows a modular architecture:

1. SqlParser: Converts SQL text into an abstract syntax tree (AST) using node-sql-parser
2. SqlCompiler: Transforms the AST into MongoDB commands
3. CommandExecutor: Executes the commands against a MongoDB database

Development

Testing

The project includes both unit tests and integration tests:

Unit Tests

Run unit tests with:

npm run test:unit

Unit tests are located in the tests/unit directory and focus on testing the parsing and compilation of SQL statements without requiring a database connection.

Integration Tests

Integration tests use testcontainers to spin up a MongoDB instance in Docker. Make sure you have Docker installed and running before executing these tests.

Run integration tests with:

npm run test:integration

Integration tests are located in the tests/integration directory and test the complete functionality with a real MongoDB database.

These tests will:

1. Start a MongoDB container
2. Load fixture data
3. Run a series of SQL queries against the database
4. Verify the results
5. Clean up the container when done

To run all tests:

npm run test

Continuous Integration

This project uses GitHub Actions for continuous integration. The CI workflow automatically runs on:

• All pushes to the main branch
• All pull requests targeting the main branch

The CI workflow:

1. Sets up Node.js (versions 16.x, 18.x, and 20.x)
2. Installs dependencies
3. Runs unit tests
4. Runs integration tests with MongoDB in a Docker container
5. Performs type checking
6. Builds the package

You can see the workflow configuration in .github/workflows/test.yml.

Documentation

Comprehensive documentation is available at queryleaf.com/docs, including:

• Detailed installation and setup guides
• In-depth explanation of supported SQL syntax
• Usage examples and best practices
• Troubleshooting and debugging guides
• Performance optimization tips

For local development, you can run the documentation site with:

# Install required packages
pip install -r requirements.txt

# Serve the documentation locally
npm run docs:serve

License

QueryLeaf is dual-licensed:

• AGPL-3.0 for open source use
• Commercial license for commercial use with embedding

For commercial licensing options and pricing, please visit queryleaf.com or contact us at [email protected].