Explore 31 boilerplates in this collection. Find the perfect starting point for your next project.
The NuxtJS template with everything you need to build your SaaS, AI tool, or web app quickly
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Complete Nuxt 4 boilerplate and launch SaaS in hours
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The Ultimate SaaS Starter Kit with all you need to ship fast.
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Accelerate your SwiftUI app development with integrated AI and secure backend solutions
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Next.js 14 app router SaaS starter kit built with Supabase
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React codebase generator for SaaS products and landing pages
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The Next.js template to quickly create your SaaS, AI tool, or any web application
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A purpose-built toolkit for building high-quality React apps
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The #1 NextJS Boilerplate for SaaS Startups
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Showing 9 of 31 boilerplates
Supabase provides a powerful data storage solution with specific transaction models, indexing strategies, and query capabilities suited for SaaS applications. Our Supabase boilerplates implement database-native features—from ACID transactions to advanced indexing—with schemas optimized for Supabase's query engine and scaling characteristics.
Supabase boilerplates are designed around the database's data modeling approach and transaction semantics. They leverage Supabase-specific features like JSONB columns, full-text search, aggregation pipelines, or partition keys depending on the database type. The schema design follows Supabase's best practices for normalization (SQL) or document structure (NoSQL), with strategic indexes on query-heavy columns. Migration systems use Supabase-native tools for version-controlled schema evolution.
Browse our collection of 31 Supabase 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.
Supabase boilerplates utilize the database's native capabilities including its transaction model (ACID for SQL, eventual consistency for NoSQL), indexing strategies (B-tree, GiST, full-text search), and advanced features like JSON columns, array types, window functions, or document queries. The schema design takes advantage of Supabase's strengths—whether that's PostgreSQL's JSONB, MySQL's full-text search, MongoDB's aggregation pipeline, or Redis's data structures.
Supabase boilerplates include production-tested schemas for multi-tenancy, user management, subscriptions, and billing. The design follows Supabase's best practices for data modeling—whether that's normalized tables with foreign keys (SQL), embedded documents vs. references (MongoDB), or partition key strategies (DynamoDB). Schemas include proper constraints, default values, and relationship management optimized for Supabase's query engine.
Supabase boilerplates implement database-specific query optimizations including strategic indexing on frequently queried columns, query plan analysis, proper use of Supabase's query features (prepared statements, query builders, aggregations), and N+1 query prevention. Connection pooling is configured for Supabase's optimal settings, and caching layers are positioned to reduce database load while maintaining data consistency.
Supabase boilerplates are structured for horizontal and vertical scaling using the database's native scaling features. This includes read replicas, sharding strategies (if applicable), connection pool sizing, and query optimization for distributed systems. The architecture supports Supabase's scaling patterns—whether that's PostgreSQL's logical replication, MongoDB's sharding, or DynamoDB's automatic partitioning.
Supabase boilerplates include migration systems using database-specific tools (Prisma migrations, Django migrations, Flyway, Liquibase, or native tools). They follow Supabase's best practices for zero-downtime deployments, backward-compatible schema changes, and data migrations. Backup strategies leverage Supabase's native backup features (pg_dump, mysqldump, mongodump) with automated scheduling and point-in-time recovery configurations.