Dancer Tunes: The Tech Stack
When I started building DancerTunes, a crowdsourced music discovery tool for dancers and DJs, I knew the tech stack had to be:
? Scalable – Able to grow as more users contribute curated dance tracks
? Efficient – Handling real-time song classifications and API requests
? Flexible – Supporting integrations with Spotify, Apple Music, Tidal, etc.
? User-Friendly – A clean and responsive UI that works across devices
After weighing my options, I settled on React, TypeScript, Node.js, GraphQL, Prisma, PostgreSQL, and Tailwind CSS, all deployed in a cloud-native architecture. Here’s why:
Frontend: React + TypeScript + Tailwind CSS
?? Component-based UI – Reusable and scalable design
?? Type safety with TypeScript – Reduces runtime errors, improves maintainability
?? Tailwind CSS for styling –?
? Utility-first approach makes UI development faster and more consistent
??? Responsive design baked in—perfect for both mobile and desktop ???
? Minimal CSS bloat—styles are generated dynamically
?? Great state management – React hooks and context make managing UI state straightforward
?? Future flexibility – Easy to extend to React Native if I build a mobile app
Backend: Node.js + TypeScript + GraphQL
?? GraphQL instead of REST – ????
? Efficient queries – Clients get exactly what they need, reducing over-fetching
???? Schema flexibility – Easier to evolve APIs without breaking clients ????
? Strongly typed API – Ensures consistency across frontend and backend
?? Node.js for its async nature – Handles API calls to streaming services efficiently
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?? TypeScript for type safety – Reduces runtime errors and improves DX
Database Layer: Prisma + PostgreSQL
?? PostgreSQL – Chosen for its reliability, scalability, and strong support for relational data
?? Prisma as the ORM – ???
? ? Type-safe queries – Eliminates SQL injection risks and improves DX ????
? Migrations are easy – Schema changes are version-controlled and structured ????
? Optimized for GraphQL – Works seamlessly with a strongly typed backend
PostgreSQL was the natural choice because:
?? Tracks, users, playlists, and dance styles all have relational data that benefit from SQL’s structure and indexing.
?? Full-text search capabilities allow users to efficiently find and filter songs.
?? Performance at scale – Handles large datasets of curated music efficiently.
Cloud-Native Approach
?? Serverless functions for scaling API requests
?? Containerized deployment for flexibility across cloud providers
?? Managed PostgreSQL hosting for better uptime and automated backups
Challenges & Trade-offs
? Managing API rate limits – Streaming services impose restrictions on external calls
? Real-time updates vs. caching – Balancing freshness of data with performance
? Handling dance-specific metadata – Ensuring the curation process remains structured
? Styling consistency – Tailwind speeds up development, but enforcing design standards still requires discipline