@trpc/server vs graphql-yoga

backend

@trpc/server

graphql-yoga

@trpc/server and graphql-yoga represent two fundamentally different approaches to building type-safe APIs in JavaScript. tRPC exposes server functions as remotely callable procedures with end-to-end TypeScript inference, eliminating the need for schema definitions or code generation. GraphQL Yoga is a modern, performant GraphQL server that enables clients to request exactly the data they need through flexible queries against a strongly-typed schema.

This comparison matters because choosing between them affects your entire API architecture, not just tooling preferences. tRPC excels in TypeScript monorepos where rapid iteration and type safety are paramount, while GraphQL Yoga provides client flexibility and ecosystem maturity for APIs serving multiple consumers or requiring service decoupling. Developers working on full-stack TypeScript applications will gravitate toward tRPC's simplicity, whereas teams building robust, client-driven APIs or microservices architectures will find GraphQL Yoga's flexibility essential.

Head-to-Head

Type Safety & Developer Experience→ @trpc/server wins

@trpc/server

tRPC provides automatic end-to-end type inference by importing server types directly into the client with zero code generation. Changes to server procedures immediately reflect in client code with IDE autocomplete and compile-time errors. The developer experience is seamless in TypeScript monorepos.

graphql-yoga

GraphQL Yoga requires schema-first development with tooling like gql.tada or GraphQLSP for typed queries. While modern tools provide excellent TypeScript support with autocomplete and validation, there's an additional build step. Type safety depends on code generation or tagged template literals.

Client Flexibility & Data Fetching→ graphql-yoga wins

@trpc/server

Clients can only call predefined server procedures that return fixed data shapes. Requesting different field combinations requires new server endpoints or overfetching with optional parameters. The server dictates available data structures, limiting client autonomy.

graphql-yoga

Clients compose queries to request exactly the fields needed from any combination of available types. A single endpoint handles arbitrary query complexity, allowing clients to evolve independently. Supports efficient batching of multiple resource requests in one roundtrip.

Runtime Performance→ @trpc/server wins

@trpc/server

tRPC has minimal overhead as it's essentially HTTP endpoints calling TypeScript functions directly. No query parsing or resolution logic. Performance is comparable to standard REST endpoints with lightweight RPC serialization.

graphql-yoga

GraphQL Yoga benchmarks show 916ms latency at 100 req/s, with response caching reducing this to 46ms at 2.2k req/s. The query parsing and resolution layer adds overhead compared to direct function calls, but optimization features like DataLoader and caching mitigate this effectively.

Bundle Size & Dependencies→ @trpc/server wins

@trpc/server

Extremely lightweight with minimal runtime dependencies. The client is a thin wrapper around fetch with TypeScript types. No schema parsing, no query builders, no complex runtime logic. Ideal for bundle-conscious applications.

graphql-yoga

GraphQL Yoga emphasizes lean dependencies but includes the GraphQL execution engine, schema validation, and query parsing. The runtime is heavier than tRPC but still optimized compared to alternatives like Apollo Server. Client libraries (like urql or Apollo Client) add significant bundle weight.

API Discoverability & Tooling→ graphql-yoga wins

@trpc/server

No standard machine-readable API schema exposed to external consumers. API documentation requires custom solutions. Introspection is limited to TypeScript types within the codebase. Third-party integrations and automated testing tools are limited.

graphql-yoga

GraphQL's introspection provides automatic API documentation through GraphiQL/GraphQL Playground. The schema serves as machine-readable API documentation. Extensive ecosystem for testing, mocking, monitoring, and third-party integrations. Federation enables distributed schema composition.

Architectural Coupling & Scalability→ graphql-yoga wins

@trpc/server

Requires TypeScript on both client and server within the same codebase or repository for type sharing. Tight coupling makes it unsuitable for microservices, multi-language environments, or APIs consumed by external parties. Scales well within monorepo boundaries.

graphql-yoga

Schema acts as a contract between services, enabling decoupled development across teams and languages. Supports Apollo Federation for distributed schema composition. External clients can consume the API without TypeScript. Architectural flexibility for microservices and third-party integrations.

Verdict

Choose @trpc/server when building full-stack TypeScript applications in a monorepo where you control both client and server. Its unmatched developer experience, automatic type safety, and minimal overhead make it the fastest path to building type-safe APIs. The tight coupling is a feature, not a bug, when your frontend and backend evolve together as a single product. tRPC eliminates boilerplate, reduces bundle size, and provides instant feedback during development—ideal for startups, internal tools, or applications where client-server boundaries are organizational, not technical.

Choose graphql-yoga when building APIs for multiple consumers, microservices architectures, or any scenario requiring client flexibility. If your API will be consumed by mobile apps, third-party developers, or independent frontend teams, GraphQL's query flexibility and schema-based contracts are essential. The mature ecosystem, introspection capabilities, and architectural decoupling justify the additional complexity. GraphQL Yoga specifically offers excellent performance characteristics while maintaining full GraphQL spec compliance and modern features like SSE subscriptions. The upfront investment in schema design pays dividends when clients need to iterate independently or when your backend comprises multiple services.

When to Use Each

If you are building a SaaS dashboard with a Next.js frontend and Node.js backend in a monorepo → use @trpc/server because the type safety and zero-boilerplate setup will accelerate development, and the tight coupling is irrelevant since you own the entire stack.

If you are building a mobile app backend that will be consumed by iOS, Android, and web clients developed by separate teams → use graphql-yoga because clients need to request different data shapes independently, and the schema provides a stable contract across platforms.

If you are creating an internal admin panel for your startup with rapid feature iteration requirements → use @trpc/server because you'll ship features faster without schema definitions, and the excellent TypeScript inference catches errors during development instead of at runtime.

If you are developing a microservices architecture where multiple backend services need to expose a unified API gateway → use graphql-yoga because it supports Apollo Federation for schema composition and works across different programming languages, maintaining service independence while providing a cohesive API.

Learn More

@trpc/server →graphql-yoga →

Head-to-Head

Type Safety & Developer Experience→ @trpc/server wins

@trpc/server

graphql-yoga

Client Flexibility & Data Fetching→ graphql-yoga wins

@trpc/server

graphql-yoga

Runtime Performance→ @trpc/server wins

@trpc/server

graphql-yoga

Bundle Size & Dependencies→ @trpc/server wins

@trpc/server

graphql-yoga

API Discoverability & Tooling→ graphql-yoga wins

@trpc/server

graphql-yoga

Architectural Coupling & Scalability→ graphql-yoga wins

@trpc/server

graphql-yoga

Verdict

When to Use Each