What is gRPC and how does it differ from REST?

By | March 25, 2023

gRPC and REST are both popular ways to build APIs for client-server communication. Here are some differences between the two:

  1. Communication Protocol: gRPC uses the HTTP/2 protocol for communication, whereas REST can use either HTTP/1.1 or HTTP/2.
  2. Data Format: gRPC uses the Protocol Buffers data format by default, which is a binary format that is more compact and efficient than JSON, the default format used by REST APIs.
  3. Performance: Due to its use of binary data format and HTTP/2 protocol, gRPC is generally considered to be faster and more efficient than REST.
  4. API Contract: In gRPC, the API contract is defined using Protocol Buffers, which makes it easier to generate code for client and server stubs. In REST, the API contract is usually defined using OpenAPI (formerly known as Swagger).
  5. Client Libraries: gRPC has official client libraries for many programming languages, whereas REST typically relies on HTTP client libraries that are already built into most programming languages.
  6. Compatibility: REST is more compatible with existing web infrastructure and can be used with web browsers, while gRPC requires special libraries and tools to be used in web browsers.

Here’s an example of a gRPC endpoint response in the Protocol Buffers data format

message Book {
  string title = 1;
  string author = 2;
  int32 published_year = 3;
}

message GetBookResponse {
  Book book = 1;
}

This message definition describes the response format for a gRPC endpoint that retrieves a book by its ID. The GetBookResponse the message has a single field book, which is of the Book type that contains details about the retrieved book such as title, author, and published year.

Here’s an example response for this endpoint:

{
  "book": {
    "title": "To Kill a Mockingbird",
    "author": "Harper Lee",
    "published_year": 1960
  }
}

In this example, the response contains the details of the book “To Kill a Mockingbird” by Harper Lee, published in 1960. The response is in the Protocol Buffers binary format, which is more compact and efficient than JSON.

In order to consume a gRPC API that uses the Protocol Buffers data format, you will need to use a Protocol Buffers library in your client application to serialize and deserialize the data.

Most programming languages have official or third-party Protocol Buffers libraries that can be used to consume gRPC APIs. For example, Google provides Protocol Buffers libraries for many programming languages, including Java, C++, Python, and Go. These libraries make it easy to define and use Protocol Buffers messages in your code.

In addition, gRPC provides language-specific code generators that can generate client-side stub code from your API definition, including the necessary Protocol Buffers message classes. This can save time and reduce errors when building client applications.

Overall, while using Protocol Buffers may add some complexity to your client-side code, it can provide significant performance benefits and is a common choice for building high-performance, scalable APIs.

To consume a gRPC API with Protocol Buffers responses from a Nuxt.js client-side application, you’ll need to use a Protocol Buffers library for JavaScript to deserialize the data. Here’s an example of how you might do this:

  1. Install a Protocol Buffers library for JavaScript in your Nuxt.js project. One popular option is protobufjs, which can be installed via NPM:
npm install protobufjs
  1. Define the Protocol Buffers message format for the response in a .proto file, and compile it into JavaScript code using the protobufjs command-line tool:
npx pbjs -t static-module -w commonjs -o api_pb.js api.proto

This will generate a JavaScript module that contains the compiled message definitions from the .proto file.

  1. Import the generated api_pb.js module and use it to deserialize the response data in your Nuxt.js code:
import { GetBookResponse } from '~/api_pb.js';
import axios from 'axios';

// Make an API request to retrieve a book by ID
axios.get('/api/books/123')
  .then((response) => {
    // Deserialize the response data using the generated message class
    const book = GetBookResponse.deserializeBinary(response.data);

    // Use the book object in your Nuxt.js application
    console.log(book.getTitle());
    console.log(book.getAuthor());
    console.log(book.getPublishedYear());
  });

In this example, we import the GetBookResponse message class from the api_pb.js module and use the deserializeBinary method to deserialize the response data from the API endpoint. We can then access the properties of the book object using getter methods generated by protobufjs.

Sharing Protocol Buffers message definitions with external consumers of your API can have some advantages and disadvantages, depending on your specific use case.

Advantages of sharing Protocol Buffers messages include:

  1. Compatibility: Because Protocol Buffers is a cross-platform data serialization format, sharing message definitions can make it easier for clients in different programming languages to consume your API.
  2. Efficiency: Using Protocol Buffers for API responses can reduce the amount of data that needs to be transmitted over the network, resulting in faster and more efficient communication.
  3. Consistency: Sharing message definitions can help ensure that clients are using the correct data format and field names, reducing the risk of errors or incompatibilities.

Disadvantages of sharing Protocol Buffers messages include:

  1. Complexity: Sharing message definitions can add complexity to your API design and development process, as you need to ensure that the messages are designed to be flexible and extensible enough to meet the needs of external consumers.
  2. Versioning: If you need to make changes to the message definitions in the future, you will need to ensure that you maintain backward compatibility with existing clients, which can be challenging.
  3. Security: Sharing message definitions can make it easier for attackers to understand the structure of your API and potentially exploit vulnerabilities.

In general, if you anticipate that your API will be consumed by clients in multiple programming languages or by third-party developers, sharing Protocol Buffers messages can be a good approach. However, if your API is intended to be used primarily within a single organization or by a small number of clients, other data formats such as JSON or XML may be sufficient.