Web Product Ecosystem

There are SO many different front-end and back-end products and services, which means there are SO many different ways to build your web product! This page is meant to give you a sneak peak into the different choices that exist. This way you are aware of all the choices that exist (and can use ChatGPT and Reddit to explore tradeoffs).

What are your needs?

For quick iteration If you want to get feedback and iterate quickly, we’d recommend you jump to the common Minimum Viable Product (MVP) Stack. This is one choice of web products that is commonly used to build a full-stack app quickly.

For more niche or production needs If you have more niche needs—like building an app that is compatible on both the phone and the web, want highly-performant low-latency back-end code, or a Python backend, you may want to explore the different web products below!

TIP: I highly encourage you to do some of the practice problems at the bottom of this page to get a better understanding of going from product design requirements (what type of functionality your product needs) and needs —> choosing a tech stack!

Table of all Web Products

Just for comprehensiveness, we put together a table that aggregates all the different products and services that can be used.

Front-end

• CSS Frameowrk: pre-designed tools** that make it easier to style websites quickly. Instead of writing all your CSS from scratch, these frameworks provide ready-to-use styles (e.g., button styles, grids
• Component Library: Collections of reusable building blocks for websites or web apps**. They provide pre-built elements like buttons, modals, navigation bars, or form fields.
• Frontend Tools: software or services that help developers design, build, and test their projects more efficiently
• Frontend Project frameworks: popular libraries that enable front-end development
• API tools: allow front-end apps to communicate with back-end servers

	Programming Languages	CSS Frameworks	Component Library	Frontend Tools	Frontend Project	API tools
Front-End	HTML, CSS, Javascript, TypescriptLess common: Dart, Elm	Tailwind, Bootstrap, Material-UI, Chakra-UI	Shadcn (built off of Tailwind),	Figma (for design), Vite, npm/nvm, Storybook (for UI components)	- React (open-source JS library) - Next JS (Framework built off of React with server-side rendering)- Svelte- Angular- Vue	GraphQL, REST API

Back-end

• Backend Frameworks: popular libraries that enable back-end development
• Backend Databases: database to store application data like user info, content, etc.
• Baas (back-end as a service): cloud-based services that provide a range of back-end development tools and services, including databases, storage, and APIs.

	Programming Languages	Backend Frameworks	Backend Databases (database to store application data like user info, content, etc.)	Baas (back-end as a service)
Back-End	Python,C++/C/C#, Go/Rust (for high performance backend, Java,Ruby, PHP,	Node.js: Express.js (build on top of Node.js to provide faster/simpler API and server-side logic),Python: Flask, Django, FastAPIOthers: Ruby on Rails	SQL: PostgreSQL, MySQL, SQLiteNoSQL: MongoDB, Firebase, CouchDBGraph Database: Neo4J, DgraphRedis (supports caching), Memcached, Cassandara, TimscaleDB, Kafka

Helpful to look into SQL vs. noSQL databases | Firebase, Supabase, Heroku, AWS Amplify, Backendless

What is back-end as a service? What is the alternative? |

Deployment

• Containerization and Orchestration: tools that help manage and deploy applications in a scalable and efficient way
• Hosting/Cloud platforms: cloud-based services that provide a range of hosting and cloud services, including storage, compute, and networking.

	Containerization and Orchestration	Hosting/Cloud platforms
Deployment	Docker, Kubernetes	AWS (Elastic Beanstalk, EC2, S3, Lambda), Google Cloud Platform (App Engine, Cloud Run, Firebase), Microsoft Azure, Heroku, Vercel, NetlifySeverless: AWS Lambda, Google Cloud Functions, Netlify FunctionsStatic: Github Pages, Vercel, Netlify

Practice Problems

We highly recommend you to use your favorite chatbot (e.g. ChatGPT, DeepSeeks, Gemini, or Claude) and Google search and Reddit to answer these questions!

Try it yourself first!

Take some time to think about each problem and research possible solutions before checking the answers. This will help you develop your tech stack decision-making skills!

1. Suppose I am trying to create a course website with good SEO. Which front-end and back-end products might be best for this?

Click to see answer

Recommended Stack:

• Frontend Framework: Next.js (built on React)

  • Provides excellent SEO through server-side rendering
  • Built-in static site generation capabilities
  • Great for content-heavy websites

• CSS Framework: Tailwind CSS

  • Highly customizable
  • Perfect for responsive design
  • Great developer experience

• Backend/CMS Options:

  • Headless CMS (like Strapi or Sanity) for content management
  • OR Static site with Markdown files
  • OR Lightweight Node.js backend with Express.js

• Database:

  • PostgreSQL for structured course data
  • OR MongoDB for flexible content structure

Why This Stack?

• Next.js’s server-side rendering ensures search engines can crawl your content effectively
• Static site generation improves performance and SEO
• Headless CMS provides easy content management for course materials

2. Suppose I am trying to create a social media app that is compatible on both the phone and the web. Which front-end and back-end products might be best for this?

Click to see answer

Recommended Stack:

• Frontend Framework: React Native Web

  • Share code between web and mobile platforms
  • Native performance on mobile
  • Consistent user experience across platforms

• UI Components:

  • React Native Paper or Native Base
  • Provides cross-platform UI components
  • Consistent design system

• Backend:

  • Node.js with Express.js or NestJS
  • GraphQL for efficient data fetching
  • WebSocket support for real-time features

• Database:

  • MongoDB for flexible social content
  • Redis for caching and real-time features

Why This Stack?

• React Native Web allows code sharing between platforms
• GraphQL reduces network requests and provides flexible data fetching
• MongoDB’s flexible schema works well for social media content

3. Suppose I am trying to create a high-performance low-latency back-end for a trading app. Which front-end and back-end products might be best for this?

Click to see answer

Recommended Stack:

• Backend Language:

  • Rust or Go for high performance
  • C++ for ultra-low latency requirements

• Backend Framework:

  • Actix-web (Rust) or Gin (Go)
  • OR custom C++ framework

• Database:

  • TimescaleDB for time-series data
  • Redis for in-memory caching
  • Kafka for event streaming

• Frontend:

  • React with TypeScript for type safety
  • WebSocket for real-time updates
  • D3.js for real-time charts

Why This Stack?

• Rust/Go/C++ provide near-native performance
• TimescaleDB optimized for time-series data
• In-memory caching reduces latency
• WebSocket maintains real-time connection

4. Suppose I am trying to create a Python-based back-end for a data analysis tool. Which front-end and back-end products might be best for this?

Click to see answer

Recommended Stack:

• Backend:

  • FastAPI or Flask for Python backend
  • Pandas for data manipulation
  • NumPy for numerical computations
  • Scikit-learn for ML features

• Frontend:

  • React or Vue.js
  • Plotly or D3.js for data visualization
  • Material-UI or Chakra UI for components

• Database:

  • PostgreSQL with TimescaleDB extension
  • OR MongoDB for unstructured data
  • Redis for caching computation results

Why This Stack?

• FastAPI provides modern async support and automatic API documentation
• Python ecosystem perfect for data analysis
• Plotly/D3.js great for interactive visualizations
• PostgreSQL handles structured data well with good Python integration

Learning from the Answers

Notice how each solution considers:

1. The specific requirements of the use case
2. Performance needs
3. Developer experience
4. Ecosystem compatibility
5. Scalability potential