Analytics Boilerplates

Explore 43 boilerplates in this collection. Find the perfect starting point for your next project.

Visit website for SaaSy Land

SaaSy Land

The ultimate, modern, open-source Next.js template with pre-configured authentication and database integration

JavaScript
TypeScript
shadcn/ui
Tailwind CSS
Prisma
Stripe
Next.js
React

Features:

AI
Analytics
Auth
Blog
Community
Contact
ContentLayer
+6 more
Visit website for Launchtoday

Launchtoday

Production-ready mobile app starter kit for launching startups faster

JavaScript
Python
TypeScript
React
PostgreSQL
Supabase
RevenueCat
Stripe
Superwall
Expo
Firebase
React Native

Features:

AI
Analytics
Auth
AWS
CI/CD
Dark Mode
i18n
+3 more
Visit website for Suparepo

Suparepo

Next.js 14 app router SaaS starter kit built with Supabase

JavaScript
TypeScript
Tailwind CSS
Supabase
Stripe
Next.js
React
tRPC

Features:

Analytics
Auth
Blog
Changelog
ContentLayer
Docs
Emails
+4 more
Visit website for AIO - React Native & Next Template

AIO - React Native & Next Template

The All-In-One Template For iOS, Android & Web

JavaScript
TypeScript
NativeWind
React
Firestore
RevenueCat
Stripe
Expo
Moti
Next.js
React Native
Reanimated
Redux Toolkit
Solito

Features:

Analytics
Auth
Auth
Dark Mode
i18n
IAP
Landing Page
+8 more
Visit website for Swift Maker

Swift Maker

The SwiftUI boilerplate that empowers serious iOS developers to transform side projects into profitable apps in record time

Swift
SwiftUI
In-App Purchases
SwiftUI
Vapor

Features:

AI
Analytics
Auth
Backend
CI/CD
Dark Mode
Deployment
+6 more
Visit website for RyzeKit Astro

RyzeKit Astro

The ultimate Astro SaaS starter kit

JavaScript
TypeScript
DaisyUI
Tailwind CSS
MySQL
PostgreSQL
SQLite
Lemon Squeezy
Stripe
Astro

Features:

Analytics
Auth
Blog
Contact
Dark Mode
Dashboard
Docs
+6 more
Visit website for AppKickOff

AppKickOff

Android App Starter-Code Generator that handles boilerplate code for rapid app development.

Java
Kotlin
Android UI
Firestore
In-App Purchases
Android

Features:

Analytics
API
Auth
Dark Mode
Navigation
Notifications
Onboarding
+2 more
Visit website for NextSaaS

NextSaaS

The All-In-One Boilerplate to Transform Your Product into SaaS in Hours

JavaScript
Python
TypeScript
DaisyUI
HeadlessUI
Tailwind CSS
MongoDB
MySQL
PostgreSQL
Stripe
FastAPI
Next.js
React

Features:

Admin
AI
Analytics
Auth
Blog
CMS
Dark Mode
+10 more
Visit website for BoilerPro

BoilerPro

SaaS boilerplate with AWS-powered features to accelerate your MVP development

JavaScript
TypeScript
Tailwind CSS
DynamoDB
Stripe
Next.js

Features:

Admin
Analytics
API
Auth
AWS
Dark Mode
Emails
+4 more

Showing 9 of 43 boilerplates

Why Choose Analytics Boilerplates?

Analytics represents a complete full-stack feature with dedicated API endpoints, database models, and UI components architected for SaaS applications. Our boilerplates with Analytics implement layered architecture patterns—separating business logic, data access, and presentation—with security measures and testing strategies specific to Analytics's functionality.

Analytics boilerplates implement full-stack architecture with service layers for business logic, repository patterns for data access, and RESTful/GraphQL API endpoints. They include Analytics-specific security measures like input validation with schema libraries (Zod, Joi), parameterized queries for SQL injection prevention, and CSRF protection. The implementation handles Analytics's real-time requirements with WebSockets or SSE when needed, includes comprehensive error handling, and follows OWASP security guidelines for Analytics's functionality.

Key Benefits

  • Analytics layered architecture
  • Analytics-specific security measures
  • Analytics API endpoint design
  • Analytics real-time capabilities
  • Analytics validation schemas
  • Analytics error handling
  • Analytics testing suite
  • Analytics performance optimization

Browse our collection of 43 Analytics boilerplates to find the perfect starting point for your next SaaS project. Each boilerplate has been carefully reviewed to ensure quality, security, and production-readiness.

Frequently Asked Questions

How is Analytics architecturally implemented?

Analytics is implemented following full-stack architecture patterns with dedicated API endpoints, database models with proper relationships, and corresponding UI components. The feature includes its own service layer for business logic, validation schemas, error handling, and event-driven updates. The architecture separates concerns between presentation, business logic, and data access layers, making Analytics maintainable and testable.

What security measures protect Analytics?

Analytics implements defense-in-depth security including input validation with schema validation libraries (Zod, Joi, Yup), parameterized database queries to prevent SQL injection, output encoding to prevent XSS attacks, CSRF token validation, and proper authentication/authorization checks. The feature includes rate limiting, audit logging, and follows OWASP security guidelines specific to Analytics's functionality.

How does Analytics handle real-time updates?

Analytics can include real-time capabilities using WebSockets, Server-Sent Events (SSE), or polling strategies depending on the use case. Real-time implementations use Socket.io, native WebSockets, or framework-specific solutions with proper connection management, authentication, and scaling considerations. The feature handles reconnection logic, message queuing, and optimistic UI updates for responsive user experience.

What API patterns does Analytics use?

Analytics's API endpoints follow RESTful principles or GraphQL patterns with proper HTTP methods, status codes, and response structures. The implementation includes request validation, pagination for list endpoints, filtering and sorting capabilities, and comprehensive error responses with meaningful messages. API versioning, rate limiting per endpoint, and OpenAPI/GraphQL schema documentation are included for Analytics's public-facing endpoints.

How is Analytics tested and validated?

Analytics includes unit tests for business logic, integration tests for API endpoints and database interactions, and end-to-end tests for critical user flows. The testing suite uses framework-specific tools (Jest, Pytest, RSpec, PHPUnit) with mocking libraries, test fixtures, and database seeding. Tests cover happy paths, error cases, edge conditions, and security scenarios specific to Analytics's functionality with proper test coverage reporting.