Different API Architectures for Modern Applications — Grow Together By Sharing Knowledge

Sandeep Agrawal
7 min readAug 16, 2023

In the rapidly evolving landscape of software development, building efficient and scalable APIs is crucial to creating successful applications. There’s no one-size-fits-all solution when it comes to choosing the right API architecture. Each architecture has its strengths and weaknesses, making it essential to understand the options available. In this blog post, we’ll delve into various API architectures, examining their features, use cases, and pros and cons.

API Architectures Overview

API architectures provide the foundation for communication between different software components. Here’s a comprehensive comparison of some popular API architectures:

Exploring API Architectures in Depth



  • Representational State Transfer (REST) is a widely adopted architectural style for designing networked applications.
  • RESTful APIs are built around a set of principles that emphasize a stateless client-server interaction through HTTP methods such as GET, POST, PUT, and DELETE.
  • They use HTTP status codes to indicate the result of the operation.


  • Widely Adopted: REST is a well-known and widely used architecture, making it easier for developers to understand and implement.
  • Simplicity: The stateless nature simplifies interactions and promotes scalability.
  • HTTP Standards: Leveraging HTTP methods and status codes provides a standardized approach.


  • Over-Fetching: RESTful APIs can lead to over-fetching of data, where clients receive more data than needed.
  • Lack of Standards: REST lacks strict standards for some aspects, leading to inconsistencies in API design.

Example: Fetching user data: GET /users/123

Developed By: Community-driven.

Application Usage: Traditional web applications, mobile apps.

Type of Input: HTTP requests.

Type of Output: JSON, XML, HTML, etc.



  • GraphQL is a query language and runtime for APIs developed by Facebook.
  • It enables clients to request exactly the data they need and nothing more.
  • GraphQL provides a single endpoint for flexible queries, allowing clients to specify the shape and structure of the response.


  • Efficient Data Retrieval: GraphQL reduces over-fetching by allowing clients to request only the required data.
  • Strong Typing: GraphQL enforces a strong typing system, ensuring data consistency.
  • Single Endpoint: Using a single endpoint simplifies API interactions for clients.


  • Server-Side Complexity: Implementing GraphQL servers can be complex, especially for handling nested queries.
  • Query Complexity: Poorly designed queries can lead to performance issues on the server.

Example: Querying user data: GET /graphql?query={user(id: "123"){name, email}}

Developed By: Facebook

Application Usage: Applications with complex data needs, dynamic data requirements

Type of Input: GraphQL queries

Type of Output: JSON



  • Simple Object Access Protocol (SOAP) is a protocol for exchanging structured information in the implementation of web services.
  • SOAP messages are formatted in XML and are typically transferred over HTTP or other application-layer protocols.


  • Strong Standards: SOAP has strong standards for communication and security.
  • Built-in Security: SOAP supports security features like encryption and authentication.
  • Interoperability: SOAP is designed for inter-platform communication and supports multiple protocols.


  • Heavyweight XML: The XML-based message format can lead to increased overhead and complexity.
  • Complex Protocol: SOAP’s complex protocol can make it less efficient compared to other lightweight alternatives.

Example: Web service call: POST /SoapEndpoint with XML payload

Developed By: Industry Consortiums.

Application Usage: Enterprise systems, legacy integrations.

Type of Input: XML payloads.

Type of Output: XML.



  • gRPC is a high-performance RPC (Remote Procedure Call) framework developed by Google.
  • It uses HTTP/2 for transport and Protocol Buffers for serialization, enabling efficient and fast communication between distributed systems.


  • High Performance: gRPC’s use of HTTP/2 and Protocol Buffers leads to efficient communication.
  • Strong Typing: Protocol Buffers enforce a strong typing system for data exchange.
  • Scalability: gRPC’s streaming capabilities make it suitable for microservices architectures.


  • Complex Setup: Setting up and configuring gRPC services can be more complex compared to REST.
  • Code Generation: The use of Protocol Buffers might require generating code for different languages.

Example: Defining and calling service methods in a strongly-typed manner.

Developed By: Google

Application Usage: Microservices, internal APIs.

Type of Input: gRPC service methods.

Type of Output: Protocol Buffers (binary)



  • WebSockets provide full-duplex communication channels over a single TCP connection.
  • Unlike traditional HTTP requests, WebSockets maintain a continuous connection that allows both the client and server to send and receive data in real-time.


  • Low Latency: WebSockets offer low latency communication suitable for real-time applications.
  • Real-Time Updates: WebSockets are ideal for applications requiring continuous data updates.
  • Efficient Communication: The persistent connection reduces overhead compared to frequent polling.


  • Complex Implementation: Implementing WebSockets can be more complex than traditional request-response APIs.
  • Not Suitable for All Use Cases: WebSockets might not be the best choice for all types of applications.

Example: Real-time chat application with continuous communication

Developed By: IETF RFCs

Application Usage: Real-time applications, live dashboards.

Type of Input: Real-time messages.

Type of Output: Real-time messages.



  • Webhooks allow applications to receive real-time data by sending HTTP POST requests to a specified callback URL.
  • They enable event-driven architectures where an external service notifies your application when certain events occur.


  • Immediate Updates: Webhooks provide immediate updates as soon as an event occurs.
  • Event-Driven Model: Applications can react to events in real-time, enabling event-driven architectures.
  • Decoupled Architecture: Webhooks decouple the event source from the consumer.


  • Reliability: Webhooks lack built-in reliability, and delivery failures can occur.
  • Security Concerns: Exposing a webhook endpoint can lead to security vulnerabilities if not properly secured.

Example: Receiving notifications: POST /webhook-callback from an external service

Developed By: Community-driven

Application Usage: Event-driven architectures, notifications.

Type of Input: External service requests.

Type of Output: HTTP responses.

GraphQL Subscriptions


  • GraphQL Subscriptions extend the capabilities of GraphQL by allowing real-time data push.
  • Clients can subscribe to specific data changes, and the server pushes updates to subscribed clients whenever relevant changes occur.


  • Real-Time Updates: GraphQL Subscriptions enable real-time data propagation to clients.
  • Efficient Data Flow: Only clients interested in specific changes receive updates.
  • Scalability: Subscriptions can be used to build scalable real-time applications.


  • Subscription Complexity: Managing subscriptions can introduce complexity to the server-side implementation.
  • Performance Considerations: Overuse of subscriptions can impact server performance.

Example: Subscribing to user updates: subscription { userUpdated(userId: "123") { name, email } }

Developed By: GraphQL Community

Application Usage: Real-time applications, notifications.

Type of Input: GraphQL subscriptions.

Type of Output: Real-time messages.



  • Open Data Protocol (OData) is a standardized protocol that allows querying and manipulating data using standard HTTP methods.
  • It promotes interoperability between different systems by providing a common way to expose and consume data.


  • Standardized Querying: OData offers standardized querying and filtering capabilities.
  • Flexible Data Access: Clients can retrieve and manipulate data in various formats.
  • Interoperability: OData supports cross-platform and cross-service integration.


  • Limited Adoption: OData’s adoption is not as widespread as other architectures.
  • Not Suitable for All Use Cases: OData might not be the best fit for all types of applications.

Example: Querying orders: GET /orders?$filter=total gt 100

Developed By: Microsoft and OASIS

Application Usage: Data APIs, querying databases

Type of Input: URL queries, HTTP methods.

Type of Output: JSON, XML, Atom, etc.



  • Falcor is a JavaScript library that optimizes data fetching by allowing clients to request only the specific data they need.
  • It uses a concept called “paths” to efficiently retrieve data from a server.


  • Reduced Over-Fetching: Falcor reduces over-fetching by fetching only required data.
  • Flexible Data Access: Clients can request data using intuitive paths.
  • Efficiency: Falcor optimizes data fetching for better performance.


  • Specific Implementation: Falcor requires both client and server implementations to work efficiently.
  • Learning Curve: Developers need to learn the concepts of paths and Falcor’s query structure.

Example: Fetching user data: get.get(["users", "123", ["name", "email"]])

Developed By: Netflix

Application Usage: Client-side data fetching, applications with complex data models

Type of Input: JSON object paths

Type of Output: JSON



  • Message Queuing Telemetry Transport (MQTT) is a lightweight publish/subscribe messaging protocol.
  • It’s designed for efficient communication between constrained devices, making it suitable for IoT applications and real-time monitoring.


  • Low Overhead: MQTT offers minimal overhead, making it efficient for low-bandwidth scenarios.
  • Real-Time Communication: MQTT supports real-time communication through publish/subscribe messaging.
  • Scalability: MQTT’s lightweight nature makes it scalable for large-scale deployments.


  • Messaging Limitation: MQTT is primarily designed for messaging scenarios and might not suit all use cases.
  • Learning Curve: Developers need to learn the concepts of MQTT topics and subscriptions.

Example: Subscribing to temperature updates: subscribe("/sensors/temperature")

Developed By: IBM and Eurotech

Application Usage: IoT applications, real-time monitoring

Type of Input: MQTT messages.

Type of Output: MQTT messages.

Choosing the Right API Architecture

Selecting the right API architecture depends on various factors, including your application’s requirements, data complexity, real-time needs, and team expertise. While RESTful and GraphQL are popular choices for a wide range of applications, gRPC, WebSockets, and Webhooks excel in specific scenarios.

Ultimately, a well-informed decision about your API architecture can lead to a more performant, scalable, and user-friendly application. Consider the characteristics of each architecture and match them to your project’s unique needs to make the right choice.

In conclusion, understanding the various API architectures empowers developers to make informed decisions that align with their project goals. Whether it’s the simplicity of RESTful APIs, the efficiency of GraphQL, the real-time capabilities of WebSockets, or the event-driven nature of Webhooks, each architecture has its place in modern application development. By carefully evaluating your requirements, you can select the architecture that best suits your project’s needs and paves the way for a successful application.

Originally published at https://techtalkbook.com on August 16, 2023.