API Design Best Practices: REST vs GraphQL vs gRPC for Different Use Cases

Selecting the right API architecture requires understanding trade-offs in performance, developer experience, and ecosystem support. This guide compares REST, GraphQL, and gRPC across technical dimensions to inform architectural decisions.

REST

REST (Representational State Transfer) uses standard HTTP methods (GET, POST, PUT, DELETE) over HTTP/1.1 or HTTP/2 with JSON payloads. It's stateless, cacheable, and universally supported.

Technical Characteristics:

• Transport: HTTP/1.1 or HTTP/2
• Serialization: JSON (text-based)
• Communication: Request/Response, Server-Sent Events (SSE), WebSockets
• Browser support: Native
• Caching: Built-in HTTP caching

Security:

• Authentication: OAuth 2.0, JWT Bearer tokens, API keys
• Authorization: HTTP headers, scope-based access control
• Transport: TLS/HTTPS mandatory for production
• Rate limiting: Implemented at gateway/proxy level

Versioning:

• URI versioning: /api/v1/users
• Header versioning: Accept: application/vnd.api+json; version=1
• Content negotiation: Media type versioning
• Deprecation: Sunset headers and documentation

Error Handling:

• HTTP status codes (4xx client errors, 5xx server errors)
• RFC 7807 Problem Details for standardized error responses
• Consistent error response structure with error codes and messages

When to Use:

• Public-facing APIs requiring broad client compatibility
• Simple CRUD operations
• Systems leveraging CDN caching
• Teams prioritizing rapid development

// REST Endpoint Example
GET /api/users/123

Response:
{
  "id": 123,
  "name": "John Doe",
  "email": "john@example.com"
}

Performance Profile:

• Latency: Baseline (higher overhead due to text serialization)
• Throughput: Moderate (limited by JSON parsing and HTTP overhead)
• CPU usage: Baseline
• Memory usage: Baseline

GraphQL

GraphQL is a query language for APIs that enables clients to request exactly the data they need. It uses a single endpoint with POST requests over HTTP/1.1 or HTTP/2.

Technical Characteristics:

• Transport: HTTP/1.1 or HTTP/2 (single endpoint)
• Serialization: JSON
• Communication: Request/Response, Subscriptions (over WebSockets)
• Browser support: Native
• Caching: Application-level required

Security:

• Authentication: Token-based (JWT) passed in HTTP headers
• Authorization: Field-level resolvers, directive-based access control
• Query complexity limiting: Prevent resource exhaustion attacks
• Query depth limiting: Mitigate nested query abuse
• Persisted queries: Prevent injection and enable caching

Versioning:

• Schema evolution: Add fields without breaking changes
• Deprecation: @deprecated directive on fields
• Non-breaking changes: Optional fields, nullable types
• Breaking changes: Require new schema version or coordination

Error Handling:

• Partial success: Errors array alongside successful data
• Error extensions: Custom error codes and metadata
• Validation errors: Returned in errors array with path information
• Resolver-level error handling: Graceful degradation

When to Use:

• Frontend applications with complex data requirements
• Aggregating data from multiple services
• Reducing over-fetching/under-fetching
• Real-time updates via subscriptions

# GraphQL Query Example
query GetUser($id: ID!) {
  user(id: $id) {
    id
    name
    email
    posts {
      title
    }
  }
}

Performance Profile:

• Latency: Variable (depends on query complexity and resolver efficiency)
• Throughput: Lower than REST for simple queries, higher for complex aggregations
• CPU usage: Higher than REST (query parsing, validation, execution)
• Memory usage: Variable (query-dependent, can spike with deep nesting)

gRPC

gRPC (Remote Procedure Call) uses Protocol Buffers for serialization and HTTP/2 for transport. It supports bidirectional streaming and is optimized for low-latency, high-throughput scenarios.

Technical Characteristics:

• Transport: HTTP/2 (required)
• Serialization: Protocol Buffers (binary)
• Communication: Request/Response, Unary, Server Streaming, Client Streaming, Bidirectional Streaming
• Browser support: Requires gRPC-Web
• Caching: Application-level required

Security:

• Authentication: TLS-based, OAuth 2.0, JWT, ALTS (Google internal)
• Authorization: Per-method interceptors, metadata-based
• Transport: TLS mandatory, mutual TLS (mTLS) for service-to-service
• Encryption: Built-in via TLS, ALTS for Google Cloud environments

Versioning:

• Protobuf field numbering: Never reuse field numbers
• Backward compatibility: Add optional fields, remove deprecated fields
• Forward compatibility: Unknown fields ignored by old clients
• Breaking changes: Require new service definition or coordination

Error Handling:

• gRPC status codes: Canonical error codes (OK, INVALID_ARGUMENT, NOT_FOUND, etc.)
• Metadata: Rich error details in response trailers
• Interceptor-based error handling: Centralized error transformation
• Status details: Structured error payloads via google.rpc.Status

When to Use:

• Internal microservice communication
• High-throughput systems requiring low latency
• Real-time streaming applications
• Bandwidth-constrained environments

// gRPC Protocol Definition
syntax = "proto3";

service UserService {
  rpc GetUser(GetUserRequest) returns (User);
}

message GetUserRequest {
  int32 id = 1;
}

message User {
  int32 id = 1;
  string name = 2;
  string email = 3;
}

Performance Profile:

• Latency: Lowest (binary serialization, HTTP/2 multiplexing)
• Throughput: Highest (efficient serialization, connection reuse)
• CPU usage: Lower than REST/JSON (binary parsing)
• Memory usage: Lower than REST/JSON (compact payloads)

Comparison Matrix

Metric	REST	GraphQL	gRPC
Latency	Baseline	Variable	Lowest
Throughput	Moderate	Variable	Highest
Payload Size	Large (JSON)	Medium (JSON)	Small (Protobuf)
Browser Support	Native	Native	gRPC-Web required
Streaming	SSE/WebSockets	Subscriptions only	Full support
Caching	HTTP-level	Custom	Custom
Security Model	OAuth2/JWT, TLS	Field-level auth, Query limits	TLS/mTLS, ALTS, Interceptors
Versioning	URI/Header/Media type	Schema evolution, Deprecation	Protobuf field numbering
Error Handling	HTTP status codes, RFC 7807	Partial errors, Error extensions	Status codes, Metadata

Decision Framework

Choose REST when:

• Building public APIs for third-party consumption
• Client compatibility is the primary concern
• Simple CRUD operations dominate
• HTTP caching provides significant value
• Standard security patterns (OAuth2) are sufficient

Choose GraphQL when:

• Frontend teams need flexible data fetching
• Multiple data sources require aggregation
• Reducing payload size through selective fields is critical
• Real-time subscriptions are needed
• Field-level authorization is required

Choose gRPC when:

• Internal microservices require maximum performance
• Low latency is a hard requirement
• Bidirectional streaming is necessary
• Network bandwidth is constrained
• Strong type safety and schema enforcement are priorities

Getting Started

1. Assess requirements: Define latency targets, throughput needs, and client ecosystem
2. Evaluate team expertise: Consider learning curve and existing infrastructure
3. Prototype: Build proof-of-concept for each candidate protocol
4. Baseline performance: Measure actual latency, throughput, and resource usage in your environment
5. Plan for evolution: Design architecture to support protocol migration if needed

Optimization priority: Baseline measurement → Caching layer → Connection optimization → Protocol migration