🗄️ SQLit

LeetCode for SQL — Practice with Real Datasets, Get Instant Feedback

🚀 Try it Live · 📖 Docs · 🤝 Contribute

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What is SQLit?

SQLit is a free, open-source SQL practice platform — like LeetCode, but purpose-built for databases. Write real queries against real schemas, get instant results in the browser, and level up from beginner to expert.

Whether you're prepping for a data engineering or analytics interview, learning SQL from scratch, or sharpening your window functions — SQLit has you covered with 412 curated problems, real-world datasets, and a built-in query optimizer.

No account required to start. No setup needed. Just open the browser and write SQL.

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Table of Contents

• Features
• Screenshots
• Tech Stack
• Project Structure
• Getting Started
• API Reference
• Roadmap
• Contributing
• License

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Features

📝 Practice Problems

• 412 curated problems across Easy, Medium, and Hard difficulties
• Covers JOINs, subqueries, CTEs, window functions, aggregations, and more
• Problems organized by concept tags and categories
• Hints, explanations, and multiple solution approaches for every problem

⚡ In-Browser SQL Engine

• Write and execute SQL directly in the browser — no setup required
• Supports SQLite (instant, client-side fallback) and PostgreSQL (production sandbox)
• MySQL dialect support via automatic syntax translation
• Sandboxed execution with timeout protection and rate limiting

🗂️ Real-World Datasets

Domain	Tables
🛒 E-Commerce	customers, orders, products, reviews
💰 Finance	accounts, transactions, portfolios, market data
🏥 Healthcare	patients, diagnoses, prescriptions, appointments

Interactive dataset explorer with schema diagrams, column types, and sample data.

🔍 Query Optimization Lab

• Visual EXPLAIN plan analyzer with color-coded node types
• See Seq Scan vs Index Scan, Nested Loop vs Hash Join
• Learn to read and optimize execution plans hands-on

🏗️ Database Design Studio

• Interactive ER Diagram Builder — drag-and-drop entities on an SVG canvas
• Add tables, columns (19 PostgreSQL types), primary keys, and foreign keys
• Export to SQL DDL with one click
• Import from SQL — paste CREATE TABLE statements and get a visual diagram
• Schema normalization guide and best practices

🎯 Interview Prep

• Timed SQL challenges simulating real interview conditions
• Company-style question sets (FAANG, startups, finance)
• Difficulty progression from phone screen to on-site level

📅 Daily Challenges

• Fresh SQL problem every day with a countdown timer
• Streak tracking to keep you consistent

📊 Profile & Progress

• GitHub-style activity heatmap showing your full solve history
• Concept badges — earn Beginner → Learner → Proficient → Expert → Master per topic
• XP system with level progression
• Track solved problems, accuracy, and streaks

🛠️ Developer Experience

• Light and dark theme with smooth toggle
• Resizable editor panels
• Syntax-highlighted SQL editor with auto-formatting
• Mobile-responsive design

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Screenshots

📸 Screenshots coming soon — try the live demo in the meantime.

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Tech Stack

Layer	Technology
Frontend	Next.js 16, TypeScript, Tailwind CSS 4
Backend	FastAPI, Python 3.12, Uvicorn
Database	PostgreSQL (production), SQLite (fallback)
State	Zustand with localStorage persistence
Auth	Auth0 (optional)
Deployment	Vercel (frontend) + Railway (backend)

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Project Structure

SQLit/
├── frontend/                  # Next.js app
│   ├── src/
│   │   ├── app/               # Pages (App Router)
│   │   │   ├── (main)/        # All authenticated routes
│   │   │   │   ├── practice/  # Problem list + solver
│   │   │   │   ├── datasets/  # Dataset explorer
│   │   │   │   ├── db-design/ # ER builder + normalization
│   │   │   │   ├── optimization/ # EXPLAIN visualizer
│   │   │   │   ├── interview/ # Interview prep
│   │   │   │   └── profile/   # Activity heatmap + badges
│   │   │   └── api/           # API route proxies
│   │   ├── components/        # Reusable UI components
│   │   ├── stores/            # Zustand state stores
│   │   └── lib/               # Utilities, API client, schemas
│   └── package.json
│
├── backend/                   # FastAPI app
│   ├── app/
│   │   ├── api/               # Route handlers
│   │   ├── core/              # Config, auth, database, rate limiter
│   │   ├── datasets/          # E-commerce, Finance, Healthcare
│   │   ├── models/            # SQLAlchemy models
│   │   └── services/          # Query executor, problem service
│   ├── Dockerfile
│   └── requirements.txt
│
└── docker-compose.yml         # Full-stack local development

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Getting Started

Prerequisites

• Node.js 18+ and npm
• Python 3.11+
• PostgreSQL 16+ (optional — SQLite fallback works out of the box)

1. Clone the repository

git clone https://github.com/Amarnath27me/SQLit.git
cd SQLit

2. Start the backend

cd backend
python -m venv venv
source venv/bin/activate        # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env            # Edit if you have PostgreSQL
uvicorn app.main:app --port 8001 --reload

The API will be running at http://localhost:8001. Test it:

curl http://localhost:8001/health
# → {"status": "ok", "service": "sqlit-api"}

3. Start the frontend

cd frontend
npm install
cp .env.local.example .env.local
npm run dev

Open http://localhost:3000 and start practicing!

4. Full stack with Docker (recommended)

docker-compose up --build

This starts the frontend, backend, and PostgreSQL together in one command.

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Deployment

Frontend → Vercel

1. Push this repo to GitHub
2. Go to vercel.com → Import your repo
3. Set Root Directory to frontend
4. Add environment variable: BACKEND_URL = your Railway backend URL
5. Deploy

Backend → Railway

1. Go to railway.com → New Project → Deploy from GitHub
2. Set Root Directory to backend
3. Add environment variables from backend/.env.example
4. Deploy — Railway auto-detects the Dockerfile

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API Reference

Method	Endpoint	Description
GET	/health	Health check
GET	/api/problems	List all problems (with filters)
GET	/api/problems/{slug}	Get problem details
POST	/api/query/execute	Execute SQL query in sandbox
GET	/api/progress	Get user progress

Full API docs available at http://localhost:8001/docs (Swagger UI) when running locally.

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Roadmap

• AI-powered query reviewer — get natural language feedback on your SQL
• Docker-based query sandbox for full execution isolation
• Skill tree visualization — see your learning path across concepts
• More datasets — education, social media, logistics, SaaS metrics
• Onboarding tutorial tour for new users
• Community solutions — browse and upvote top solutions per problem
• SQL interview simulator — live timer, hints disabled, score report

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Contributing

Contributions are welcome! If you'd like to help:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Commit your changes: git commit -m 'Add your feature'
4. Push to the branch: git push origin feature/your-feature
5. Open a Pull Request

High-priority areas:

• Adding new datasets (education, social media, logistics)
• More SQL problems (especially hard-level window function challenges)
• AI-powered query review integration
• UI/UX improvements

Please open an issue first for major changes so we can discuss the approach.

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License

This project is open source and available under the MIT License.

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Built with ❤️ for the SQL community by Amarnath Allamraju

⭐ If SQLit helped you, consider starring the repo!