System Design Basics for Backend Developers · 강의

GraphQL과 gRPC

유연한 데이터 조회를 위한 GraphQL과 고성능 통신을 위한 gRPC 등 대안적인 API 방식을 살펴봅니다.

GraphQL과 gRPC은(는) CoddyKit의 무료 System Design Basics for Backend Developers 강의입니다. 이것은 4개 중 2번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 System Design Basics for Backend Developers 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. System Design Basics for Backend Developers 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

Beyond REST: GraphQL & gRPC

RESTful APIs are widely used, but they aren't always the perfect fit for every scenario.

Sometimes, you need more control over data fetching or require extremely high performance for inter-service communication.

This lesson explores two powerful alternatives: GraphQL and gRPC.

REST's Data Fetching Hurdles

Traditional REST APIs often lead to two common issues:

Over-fetching: Receiving more data than needed in a single request, wasting bandwidth.
Under-fetching: Needing to make multiple requests to different endpoints to gather all required data.

This can be inefficient, especially for mobile clients or complex UIs.

GraphQL: Query Exactly What You Need

GraphQL is a query language for your API, and a server-side runtime for executing those queries.

It empowers clients to request precisely the data they need, eliminating over-fetching and under-fetching.

Think of it as filling out a form for your data request, rather than accepting a pre-defined bundle.

Defining Data with GraphQL Schema

Every GraphQL API is built around a schema. This schema defines all the types of data and operations (queries, mutations) available.

It acts as a contract between the client and the server, ensuring clients know exactly what they can ask for.

Here's a simple example:

type User {
  id: ID!
  name: String!
  email: String
  posts: [Post]
}

type Post {
  id: ID!
  title: String!
  content: String
  author: User!
}

Fetching Data with GraphQL Queries

Clients use GraphQL queries to fetch data. They specify the exact fields they want from the available types defined in the schema.

This means a single query can replace multiple REST requests.

See how we only ask for name, email, and post titles:

query GetUserAndPosts {
  user(id: "123") {
    name
    email
    posts {
      title
    }
  }
}

Changing Data with GraphQL Mutations

Just as queries fetch data, mutations are used to modify data on the server. This includes creating, updating, or deleting records.

Mutations also return data, often the newly created or updated object, confirming the change.

Here's an example to create a new post:

mutation CreatePost($title: String!, $authorId: ID!) {
  createPost(title: $title, authorId: $authorId) {
    id
    title
  }
}

gRPC: High-Performance RPC

gRPC (Google Remote Procedure Call) is an open-source framework for high-performance communication between services.

Unlike GraphQL, gRPC is more commonly used for internal microservice communication where speed, efficiency, and strict contracts are paramount.

It's built on HTTP/2 for transport and Protocol Buffers for message serialization.

Protocol Buffers: gRPC's IDL

gRPC uses Protocol Buffers (Protobuf) as its Interface Definition Language (IDL) and its underlying message interchange format.

Protobuf defines the structure of your data and the service interfaces in a language-agnostic way.

This definition is then used to generate client and server code in various languages.

syntax = "proto3";

package greeter;

service Greeter {
  rpc SayHello (HelloRequest) returns (HelloReply);
}

message HelloRequest {
  string name = 1;
}

message HelloReply {
  string message = 1;
}

gRPC: Binary, HTTP/2, Streaming

Key features of gRPC for high performance:

HTTP/2: Enables multiplexing (multiple requests over one connection) and bidirectional streaming.
Binary Serialization: Protobuf serializes data into a compact binary format, which is faster and smaller than JSON.
Code Generation: Automatically generates client and server stub code from .proto definitions, simplifying development.

Choosing Between GraphQL & gRPC

When to use which?

GraphQL: Ideal for flexible, client-facing APIs where clients need to define their data requirements. Excellent for mobile apps and complex UIs.
gRPC: Best for high-performance, low-latency inter-service communication (e.g., microservices), or when strict contracts and efficient data transfer are critical.

They solve different problems and can even be used together in a larger system!

Quick Check: API Styles

Consider a scenario where you are building a new mobile application with a complex UI that needs to fetch varied data from a backend with minimal network requests. Which API style would be most suitable for the client-server communication?

Recap: Flexible & Fast APIs

In this lesson, we explored two powerful API alternatives: GraphQL and gRPC.

GraphQL provides a flexible query language, allowing clients to fetch precisely the data they need, tackling over- and under-fetching issues.
gRPC offers a high-performance, binary communication framework, ideal for efficient inter-service communication using HTTP/2 and Protocol Buffers.

Understanding their strengths helps you choose the right tool for different system design challenges.

자주 묻는 질문

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유연한 데이터 조회를 위한 GraphQL과 고성능 통신을 위한 gRPC 등 대안적인 API 방식을 살펴봅니다. 브라우저에서 직접 실행하는 실습 코드로 System Design Basics for Backend Developers을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

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사전 경험은 필요하지 않습니다. CoddyKit의 System Design Basics for Backend Developers은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 2번째 강의입니다.

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