Flexible component library with massive ecosystem. Ideal for SPAs and complex UIs.
Best for: Large teams, complex state management
Full-featured framework with dependency injection, routing, and forms built-in.
Best for: Enterprise apps, strict architecture
React framework with SSR, SSG, and API routes. Great DX with file-based routing.
Best for: SEO-focused apps, full-stack React
Compiler-based framework with no virtual DOM. Minimal bundle size, true reactivity.
Best for: Performance-critical apps, small bundles
Cross-platform UI toolkit with native performance. Single codebase for web, mobile, desktop.
Best for: Cross-platform apps, custom UI
Frontend Clash 2026
React, Angular, Next.js, Svelte & Flutter
Build the same real-world application in all 5 frameworks. Compare approaches, understand trade-offs, and master modern frontend development. Updated with every major framework release.
- One app built 5 ways
- Lifetime free updates
- Certificate of completion
Usage
Percentage of developers who have done extensive development work with each framework in the past year.
- Hiring: Popular frameworks = larger talent pool
- Support: More users mean better community help
- Longevity: High adoption reduces abandonment risk
Developer Satisfaction
How developers feel about the frameworks they've used. Admired means they want to continue using it. Desired means they want to learn it.
- Retention: Happy devs stay longer on projects
- Productivity: Loved tools boost motivation
- Future: High desire = growing ecosystem
Lighthouse Metrics
Core Web Vitals and performance scores
First Contentful Paint
Time until the first content is rendered. Critical for perceived performance.
- Bounce Rate: 53% leave if load > 3s
- Core Web Vital: Impacts Google rankings
Test: lighthouse --only-categories=performance
Largest Contentful Paint
Time until the largest content element is visible. Key Core Web Vital.
- User Perception: When page feels "loaded"
- SEO: Google's primary loading metric
Good: <2.5s | Needs work: <4s | Poor: >4s
Time to Interactive
Time until page is fully interactive and responds to user input.
- Frustration: Unresponsive buttons annoy users
- Hydration: SSR apps must hydrate quickly
Good: <3.8s | Needs work: <7.3s | Poor: >7.3s
Total Blocking Time
Sum of blocking time between FCP and TTI. Measures main thread blocking.
- Interactivity: High TBT = laggy interactions
- Core Web Vital: Lab proxy for INP
Good: <200ms | Needs work: <600ms | Poor: >600ms
Cumulative Layout Shift
Measures visual stability. Quantifies unexpected layout shifts.
- UX: Prevents accidental clicks
- Core Web Vital: Key stability metric
Good: <0.1 | Needs work: <0.25 | Poor: >0.25
Speed Index
How quickly content is visually displayed during page load.
- Perceived Speed: Visual completeness over time
- User Experience: Faster feels better
Good: <3.4s | Needs work: <5.8s | Poor: >5.8s
Build & Bundle
Production build size and compilation time
Bundle Size
Production bundle size after tree-shaking and minification.
- Mobile: Crucial for slow connections
- Costs: Less bandwidth = lower CDN bills
Test: npm run build && du -sh dist
Build Time
Time to create a production build. Affects DX and CI/CD speed.
- DX: Slow builds kill developer flow
- CI/CD: Build minutes cost money
Test: time npm run build
Runtime
Memory usage during execution
Memory Usage
Browser memory consumption with 100 items. Lower = better on low-end devices.
- Budget Phones: 2GB RAM common
- Tab Crashes: High memory kills tabs
Test: DevTools → Memory → Heap snapshot
Battle-tested enterprise framework with extensive ecosystem and strong typing.
Best for: Enterprise systems, microservices
Modern Python framework with auto-generated docs, async support, and type hints.
Best for: AI/ML APIs, rapid prototyping
Angular-inspired Node.js framework with decorators, DI, and modular architecture.
Best for: Full-stack TS teams, structured APIs
Cross-platform, high-performance framework with excellent tooling and Azure integration.
Best for: Windows shops, Azure deployments
Minimalist Go framework with blazing performance. Low memory, fast cold starts.
Best for: High-throughput APIs, cloud native
Backend Clash 2026
Spring Boot, FastAPI, NestJS, .NET Core & Gin
Build the same real-world API in all 5 frameworks. Compare approaches, understand trade-offs, and master modern backend development. Updated with every major framework release.
- One API built 5 ways
- Lifetime free updates
- Certificate of completion
Usage
Percentage of developers who have done extensive development work with each framework in the past year.
- Hiring: Popular frameworks = larger talent pool
- Libraries: More integrations and plugins available
- Enterprise: Proven in production at scale
Developer Satisfaction
How developers feel about the frameworks they've used. Admired means they want to continue using it. Desired means they want to learn it.
- Maintenance: Happy devs write better code
- Velocity: Loved tools boost team speed
- Recruiting: Exciting tech attracts talent
Build & Deployment Metrics
Size, dependencies, and startup characteristics
Build Size
Production build size including runtime dependencies. Smaller bundles mean faster deployments and lower storage costs.
- Containers: Smaller images = faster pulls
- Serverless: Affects cold start time
- Storage: Lower registry/artifact costs
Dependencies Count
Number of direct and transitive dependencies. Fewer dependencies mean smaller attack surface and easier maintenance.
- Security: Each dep is a potential vulnerability
- Updates: More deps = more breaking changes
- Auditing: Easier compliance with fewer deps
Dependencies Size
Total disk space used by installed packages. Important for container images and deployment artifacts.
- CI/CD: Faster npm/pip install in pipelines
- Docker: Smaller base images = faster deploys
- Disk: Lower storage costs on dev machines
Lines of Code
Lines of code required for equivalent functionality (CRUD API). Measures framework verbosity and developer productivity.
- Productivity: Less code = faster delivery
- Bugs: Fewer lines = fewer places for bugs
- Onboarding: Smaller codebases are easier to learn
Cold Start
Time from process start to first request served. Critical for serverless deployments and auto-scaling scenarios.
- Serverless: Lambda/Functions bill cold starts
- Auto-scaling: Fast spin-up handles spikes
- Deployments: Quick restarts = less downtime
Build Time
Time to create a production release build. Faster builds improve developer experience and CI/CD pipeline speed.
- DX: Slow builds kill developer flow
- CI/CD: Faster builds = quicker deployments
- Costs: Build minutes cost money on CI platforms
Resource Metrics
Memory usage under load
Memory Usage
RAM consumption under load. Lower memory enables more instances per host and reduces cloud costs.
- Cloud Bills: RAM is expensive on AWS/GCP
- Containers: More pods per node = savings
- Stability: Low memory prevents OOM kills
Latency Distribution
Response time percentiles comparison
Latency Percentiles
API response time in milliseconds. Lower = faster. Smaller gaps between percentiles indicate more consistent performance under load.
- P50: Median - half of requests are faster
- P95: 95% faster - 1 in 20 sees this delay
- P99: 99% faster - worst 1% of requests
Requests Per Second
Maximum throughput under load. Higher is better. Tests how many API requests the server can handle per second.
- Scale: Handle traffic spikes without crashing
- Cost: Fewer servers needed for same load
- Viral: Ready when your app trends on social
Concurrent Connections
Maximum simultaneous connections before degradation. Critical for high-traffic applications and real-time features.
- Real-time: Chat apps need many open sockets
- Peak Hours: Handle lunch-time traffic surges
- Gaming: Multiplayer needs stable connections