Web API vs. REST API

In modern web and app development, Application Programming Interfaces (APIs) are the backbone of systems, applications, and platforms. Among the numerous types of APIs available, REST and Web APIs are terms that developers often encounter.

Web API vs. REST API—is there a difference? This guide delves into these concepts to help developers decide which API protocol makes sense for their specific use cases.

Summary of differences: Web API vs. REST API

What are web APIs?

A Web API is an interface that allows applications to interact with each other over HTTP or HTTPS protocols. It provides a set of rules and protocols for building and interacting with software applications. There are many types of Web APIs like REST, SOAP, and GraphQL (see below). The terms Web API and REST API are sometimes used interchangeably, but it is important to note that all Web APIs are not REST APIs. Technically, Web API is an umbrella term for many different types of APIs that use HTTP as the communication protocol—as summarized in the table below.

Let’s explore these common types in detail below.

REST API

A REST API is a type of Web API that adheres to the principles of REST. REST principles emphasize statelessness, easy-to-use and self-descriptive messages, and a layered structures to facilitate the caching of components to help scaling. We delve into the principles in a later section of this article.

Here's a Python code example of a RESTful Web API.

from flask import  Flask, jsonify

app = Flask(__name__)

@app.route('/users', methods=['GET'])
def get_users():
    return jsonify({'users': ['Alice', 'Bob']})

if __name__ == '__main__':
    app.run()

This code follows REST principles as it uses HTTP methods and stateless communication.

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SOAP API

Simple Object Access Protocol (SOAP) is a protocol for exchanging structured information to implement web services. Unlike REST, SOAP relies on XML-based messaging and strict standards.

Here's a Python code example of a SOAP Web API:

from spyne import Application, rpc, ServiceBase, String
from spyne.protocol.soap import Soap11
from spyne.server.wsgi import WsgiApplication

class HelloWorldService(ServiceBase):
    @rpc(String, _returns=String)
    def say_hello(ctx, name):
        return f"Hello, {name}"

application = Application([HelloWorldService], 'spyne.examples.hello.soap',
                          in_protocol=Soap11(validator='lxml'),
                          out_protocol=Soap11())

wsgi_application = WsgiApplication(application)

GraphQL API

GraphQL is a query language for APIs that provide a more flexible and efficient approach to data retrieval. REST exposes multiple endpoints for different resources, but GraphQL exposes a single endpoint for all interactions. This single endpoint allows clients to request exactly the data they need, down to individual fields on objects. 

In REST, you would typically have to make multiple requests to different endpoints to gather related data. For example, if you wanted to get information about a book and its author, you might first fetch the book details from a /books/{id} endpoint and then fetch the author details from an /authors/{id} endpoint. In GraphQL, you can fetch all this related data in a single query, specifying exactly what you need.

Suppose you have a GraphQL API that provides information about books and authors. You want to fetch a book's title and its author's name. Here's a GraphQL query that does just that.

query {
  book(id: "1") {
    title
    author {
      name
    }
  }
}

This query asks for the book with id of "1", and for that book, it requests the title and the name of the author.

On the server side, you might handle this query with a resolver function written in Python using a library like Graphene. Here's a simple example:

import graphene

class Author(graphene.ObjectType):
    name = graphene.String()

class Book(graphene.ObjectType):
    title = graphene.String()
    author = graphene.Field(Author)

class Query(graphene.ObjectType):
    book = graphene.Field(Book, id=graphene.String())

    def resolve_book(self, info, id):
        # Fetch the book from your data source using the provided id
        book_data = get_book_by_id(id)
        return Book(title=book_data['title'], author=Author(name=book_data['author_name']))

schema = graphene.Schema(query=Query)

This code defines the GraphQL types Author and Book and a query that allows you to fetch a book by its id. The resolve_book function is responsible for actually fetching the data; in a real-world application, you would implement get_book_by_id to retrieve the data from your database or other data source.

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Architecture: Non-RESTful web API vs. REST API

The key difference between REST and Non-REST APIs is how they process data. Let’s explore the details below.

REST APIs

RESTful APIs allow easy data ingestion through standard HTTP methods like GET, POST, PUT, and DELETE. This standardization makes it easier to integrate with various platforms and tools. 

Stateless

Statelessness ensures the server does not need to retain information about the client's state between requests. Each request from a client contains all the information needed to process it, simplifying data handling. Statelessness is the main design consideration for REST APIs— if the server doesn’t need to know or remember anything, then most likely, the best choice for your use case is a REST API.

Scalable  

The stateless nature of REST allows for greater scalability, as you can easily add new instances without worrying about shared state. REST allows simple microservices deployed using AWS Lambda, GCP Cloud Functions, or Azure Functions to handle more than millions of requests per second with serverless technology.

Easy to use

The use of standard HTTP methods in RESTful APIs simplifies the process of sending and receiving data. For example, creating a simple API in Flask or with a package like FastAPI can be done in less than 15 lines of code with only one import statement. This simplicity makes it easier for developers to get started and facilitates collaboration among team members. When everyone is on the same page about how data should be ingested and processed, it accelerates the development cycle and helps to maintain code quality.

Non-RESTful web APIs

Non-RESTful APIs, such as SOAP, may require specific protocols or standards for data ingestion.

Complexity

Non-RESTful APIs like SOAP may require specific headers and XML-based request bodies, adding complexity to data ingestion.

Statefulness 

Some non-RESTful APIs maintain state between requests, which complicates data handling but may be necessary for specific use cases like web sockets deployed for services like data streaming or gaming applications.

Security

Protocols like SOAP often include built-in security standards, such as WS-Security, which can be beneficial for secure data transmission. Security is one of the reasons nowadays that developers choose a non-RESTful web API over a REST.

Flexibility

Non-RESTful APIs offer more flexibility in handling complex operations and transactions, particularly in enterprise environments.

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API Performance: Non-RESTful web API vs. REST API 

Apart from architecture, performance is a key consideration in the non-RESTful Web API vs. REST API debate.

REST APIs

REST APIs often perform better due to their stateless nature and reliance on standard HTTP methods. They typically use JSON, which is generally more lightweight than XML in SOAP and leads to faster data transmission and processing. They also leverage HTTP caching mechanisms to improve response times. Clients or intermediate proxies can cache responses for faster retrieval. 

The stateless nature of REST reduces server overhead, as there's no need to manage client sessions. This can lead to better performance and scalability. As mentioned before, serverless technology dramatically decreases the costs of performant REST APIs.

Non-RESTful web APIs

Non-RESTful APIs offer specialized performance features tailored to specific use cases. Some non-RESTful APIs allow batching multiple requests into a single HTTP request, reducing overhead and improving performance. They may also support specific compression algorithms that reduce transmitted data's size and improve transmission speed. You can also design them with specific performance optimizations tailored to the unique requirements of a particular system or use case.

For example, compared to REST, the level of granularity GraphQL provides is particularly useful for reducing over-fetching and under-fetching of data and improving web application performance. Clients can request exactly the data they need, nothing more, nothing less.

Additionally, GraphQL APIs are strongly typed, making it easier to validate queries and responses. GraphQL provides a powerful alternative to REST for various use cases, especially those requiring complex queries and multiple related resources, by offering a more flexible query language.

Use cases: Non-RESTful web APIs vs. REST API 

It can be challenging to choose a specific API type as different use cases have different nuances to consider. We have summarized suggestions in the table below.

REST APIs

Non-RESTful web APIs

Monitoring Web API performance with Catchpoint

Monitoring the performance of both RESTful and non-RESTful Web APIs is required for ensuring a positive digital user experience. Traditional monitoring solutions and open-source tools fail to capture the complex web of third-party dependencies.

Catchpoint is a platform designed to monitor the availability and performance of the complete set of components traversed by a transaction between the end-user and the API. This holistic approach contrasts with typical application performance monitoring (APM) approaches taken by conventional vendors that focus only on the software components controlled directly by the service provider. 

For example, an API call may be slow because the DNS was slow to resolve the request API endpoint address, the content delivery network (CDN) may be slow, or the many internet service providers along the transaction path may have routing storms. Catchpoint monitors the transactions from an end-user perspective using both real-user monitoring (RUM) and synthetic monitoring (emulated transactions) to ensure the application is responsive at all times while pinpointing the root cause of a slowdown, whether it’s within the purview of the service provider or caused by third-party service providers. 

By offering synthetic monitoring for all possible platforms (e.g., different desktops and mobile devices) from hundreds of service provider networks, software vendors can ensure all customers are experiencing a positive user experience. With the new Catchpoint Tracing product, you can also monitor APIs at the server/backend side, understand upstream or downstream application dependencies, and optimize inefficient code for enhanced API performance. 

Here are some ways DevOps teams can benefit from Catchpoint’s API monitoring solution:

• Capture availability, performance, and custom KPI metrics for regression analysis and long-term trend analysis. 
• Run API transactions for functional testing payloads and parse for expected responses.
• Assure service delivery across a complex mesh of API endpoints, microservices, and gateways for data integrity validation.
• Monitor the comprehensive transaction path, including all of the components that make up the public internet, which can cause slowdowns often blamed on the software as a service provider.
• Manage API incidents in real-time before end-users call to complain about performance problems.

Catchpoint's unique approach to API monitoring makes it a valuable tool for developers working with RESTful and non-RESTful Web APIs. By supporting the OpenTelemetry approach, Catchpoint ensures developers won’t create dependencies on proprietary instrumentation technologies.

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Conclusion‍

Web APIs can be both RESTful and non-RESTful. There are more types of non-RESTful APIs, and while RESTful APIs are the most common approach, being prepared to utilize and understand both is essential for developers. Choosing between non-RESTful Web API vs. REST API depends on the specific requirements of the application and the use cases it needs to support. 

Most modern applications have RESTful APIs used in some capacity, so if you are new to learning about API deployment and development, this is the most logical place to start. Additionally, with the improvement of serverless deployment/hosting technologies, REST APIs are frequently the most cost-effective and lean approach to development, offering simplicity, scalability, and standardization. Nonetheless, non-RESTful Web APIs may provide more flexibility, security, and tailored functionality for complex or specialized tasks.