How to Design APIs Like a Pro: REST, GraphQL, gRPC, and Learning with AI on ASI Biont

## Introduction API design is an art that requires a deep understanding of architectural styles, data transfer protocols, and business requirements. Today, developers increasingly face a choice between REST, GraphQL, and gRPC. Each of these approaches has its strengths and limitations. But how do you master all three technologies without drowning in a sea of information? The answer lies in systematic learning using AI. On the ASI Biont platform, the course **"API Design (REST, GraphQL, gRPC)"** offers a unique format: AI generates personalized lessons, helping you master **OpenAPI specifications**, industry best practices, and the nuances of each protocol. In this article, we will break down the key aspects of API design and explain how AI accelerates the learning process. ## Why REST Remains the Industry Standard? REST (Representational State Transfer) is an architectural style that has dominated web development for over 20 years. Its popularity stems from simplicity and versatility. REST uses HTTP methods (GET, POST, PUT, DELETE) and resources as URLs. For example, to get a list of users, you send a GET request to `/users`. **Advantages of REST:** - Simplicity of implementation and understanding. - Broad support by tools (Postman, Swagger). - HTTP-level caching. - Mature ecosystem. However, REST is not without drawbacks. For instance, it often leads to over-fetching (excessive data loading) or under-fetching (insufficient loading), where the client has to make multiple requests to get the needed information. This is where GraphQL enters the scene. ## GraphQL: Query Flexibility and Traffic Minimization GraphQL, developed by Facebook in 2015, solves the problem of data redundancy. The client itself determines which fields it needs. For example, a query: ```graphql query { user(id: 1) { name email } } ``` Will return only the name and email, without extra fields. This is especially useful for mobile applications with limited traffic. **Key Features of GraphQL:** - Single endpoint (`/graphql`). - Strong typing through a schema. - Ability to combine data from different sources. But GraphQL is more complex to cache and requires more careful schema design. For high-performance systems, gRPC is often chosen. ## gRPC: High Performance and Binary Protocol gRPC is a framework from Google based on HTTP/2 and Protobuf (Protocol Buffers). It provides 5-10 times higher data transfer speed compared to REST due to binary serialization and request multiplexing. gRPC is ideal for microservice architecture and real-time applications. **Example of service definition in a .proto file:** ```protobuf service UserService { rpc GetUser (UserRequest) returns (UserResponse); } message UserRequest { int32 id = 1; } message UserResponse { string name = 1; string email = 2; } ``` **Pros of gRPC:** - High performance. - Support for streaming. - Automatic client generation. **Cons:** - Debugging complexity. - Limited browser support (requires gRPC-Web). ## Comparison of REST, GraphQL, and gRPC: Table | Criterion | REST | GraphQL | gRPC | |-----------|------|---------|------| | Data format | JSON/XML | JSON | Protobuf (binary) | | Protocol | HTTP/1.1 | HTTP/1.1 | HTTP/2 | | Query flexibility | Low | High | Medium | | Performance | Medium | Medium | High | | Caching | Built-in | Complex | None | | Ideal scenario | CRUD applications | Complex UIs | Microservices | ## How AI Helps in Learning API Design on ASI Biont? The course **"API Design (REST, GraphQL, gRPC)"** on the **ASI Biont** platform uses AI to generate learning materials. Instead of reading static textbooks, you receive adaptive lessons that adjust to your level. AI analyzes your answers and progress, offering additional examples or in-depth topics. **How it works:** 1. You start with the basics—learning RE

How to Design APIs Like a Pro: REST, GraphQL, gRPC, and Learning with AI on ASI Biont

Comments

Recent articles

AI Translation: How to Translate a Website into 10 Languages in a Minute Using Neural Networks

Internet Search and Parsing JS Sites: web_search for Data, browser_scrape for SPA

AI in E-commerce: How Training on Wildberries and Ozon Is Changing the Sales Approach in 2026

AI Tester (AI Auto-Tests): How AI is Changing Training and Test Automation

AI Tester (Auto Tests AI): How Learning with AI Changes the Approach to Code Quality

Arduino, IoT and Embedded Systems: How AI is Transforming Learning in 2026

AI Agents in Practice: How Multi-Agent Systems Are Transforming Learning with AI at ASI Biont

German Language with AI: How Artificial Intelligence Accelerates Learning and Preparation for the Goethe-Zertifikat

Rust for Web (Actix/WASM): How AI Training on ASI Biont Is Changing Web Development