REST vs gRPC: Which API Approach Fits Your Stack?

Publishing APIs
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I just dropped a new video comparing REST and gRPC. This isn’t just about what they are, but how and when to use them based on real-world needs. If you’ve been deciding between the two, or considering using both, this will give you a clear direction.

:fork_and_knife: Fork the Postman workspace here
:link: Watch the video:

You can explore REST and gRPC versions of the same API and test them side by side.

I’m dropping more details in the comments :down_arrow: including a step-by-step walkthrough and tips for testing. Would love to hear how you’re using REST or gRPC in your own work.

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Thanks for watching the video and checking out the workspace. If you want a deeper dive or prefer to follow along step by step, here’s everything you need to know.

What the video covers

In the video, I use a simple but effective metaphor to explain how REST and gRPC differ. Think of REST as a pickup truck and gRPC as a Formula 1 car. One is dependable and works in just about any environment. The other is built for speed and precision but needs the right setup and a more advanced skill set. This comparison goes beyond performance. It’s really about choosing the right approach based on your architecture, team workflows, and product goals.

I cover real-world use cases where REST makes the most sense, like public APIs, broad compatibility, and low-friction onboarding. Then I dive into scenarios where gRPC excels, such as internal microservices, low-latency systems, and real-time streaming applications. You’ll also see how modern teams are using both, depending on the layer or consumer of the API.

What’s inside the workspace

To help you explore both options, I built a public Postman workspace with two versions of the same Car Dealership API. One version uses REST and the other uses gRPC. You can fork the workspace and start making requests immediately.

Each version includes common operations like adding, listing, updating, and deleting vehicles. The REST implementation uses HTTP methods with JSON payloads. The gRPC version is built with Protocol Buffers and includes all four communication styles: unary, server streaming, client streaming, and bidirectional streaming.

The goal is to give you a practical, side-by-side view of how each works so you can evaluate them based on your own use case.

Step-by-step tips to explore

  1. Start with the REST API folder. These requests use standard HTTP and are easy to scan and understand. They’re a good baseline for comparison, especially when it comes to readability and debugging.
  2. Move over to the gRPC folder. Begin with the unary calls, which function similarly to REST. Once you’re comfortable, check out the streaming examples. Start with server streaming, then client streaming, and finish with bidirectional.
  3. As you test the streaming calls, pay attention to how the flow of data changes. Streaming isn’t just about speed. It enables different kinds of interaction patterns that are useful in chat apps, live dashboards, and real-time services.
  4. Compare the structure and efficiency of JSON versus Protocol Buffers. You’ll see how gRPC handles serialization, contracts, and type safety in a very different way from REST.
  5. Try making small edits to the .proto file and watch how Postman reflects those changes. This is a good way to understand how gRPC reinforces structure early in the development process, reducing bugs before they hit production.

If you’re using REST, gRPC, or both in your stack, I’d love to hear how it’s going. What patterns are working for your team? Are there edge cases or pain points that led you to switch between the two?

Drop your thoughts or questions here. I’m always up to trade notes or help troubleshoot.