Beyond REST: How to Choose Between gRPC, GraphQL, Events, and More

Smart API Design Guide

When REST Stops Being Enough

At first, REST felt like the perfect choice.

Our first micro service was straightforward just JSON over HTTP. Frontend devs loved how easy it was to use. Backend engineers appreciated the simplicity. It seemed REST could do no wrong.

But our systems grew. Suddenly REST wasn’t enough. Each new client added complexity. Endpoints got crowded, fetching turned chatty, versioning politics surfaced, and deployments frequently disrupted existing users.

We’d reached REST’s breaking point but not because it was bad, but because we needed it to handle scenarios it wasn't built for.

We realized REST was just one of several powerful API paradigms. Our journey led us beyond REST, exploring GraphQL, gRPC, and event-driven architectures. Here's what we discovered and how you can pick the right tool at the right time.

for example: Below diagram shows a client requesting user data via clearly defined endpoints. Data travels back synchronously in simple JSON.

// REST Call
GET /users/123
Response → {id:123, name:"John", email:"john@example.com"}

---

GraphQL: Frontend Flexibility

REST has fixed endpoints. The backend decides what data clients can access. But what if your frontend needs to combine data from multiple services to render a single screen?

We had this exact issue and dashboard needing data from five distinct services. REST calls piled up quickly, adding complexity and latency.

GraphQL solved that. It reversed the control. Instead of backends deciding data structures, frontends could precisely define their data queries. One clear request gave us exactly what we needed.

But freedom always comes at a price. GraphQL forced us to carefully optimize backend resolvers and watch out for query complexity.

Ideal For:

• Complex UIs needing flexible data shaping

• Reducing frontend-backend friction and roundtrips

for example: Below diagram shows client fetches customized data from multiple services in one query, reducing multiple round trips and excess data.

// GraphQL Query
query {
  user(id: "123") {
    name
    orders(limit: 3) {
      id
      total
    }
  }
}

---

gRPC: Fast Internal Pipes

Internally, things moved fast and really fast. One of our billing processes was making over 100,000 REST calls per minute. REST’s overhead was killing performance.

Switching to gRPC drastically cut latency nearly halving it overnight. Protocol Buffers streamlined payloads into efficient binaries, and schema-first contracts made APIs clearer.

However, gRPC wasn't as intuitive as REST. Debugging required more advanced tooling, and onboarding new developers became a bit harder.

Ideal For:

• High-performance, internal microservice communication

• Latency-sensitive use-cases

for example: Below diagram illustrates internal services communicating rapidly using lightweight binary payloads and well-defined schemas.

// gRPC Service Definition
service BillingService {
  rpc GetInvoice (InvoiceRequest) returns (InvoiceResponse);
}

---

Event-Driven: Decoupling at Scale

One day, a simple missed webhook triggered cascading failures across our system. Tight coupling was dangerous, and REST couldn’t fix that.

We shifted towards Kafka and event-driven architecture, enabling loose coupling through asynchronous messaging. When a new user signed up, events triggered parallel, independent processes: sending emails, initiating billing, and logging analytics without direct inter-service calls.

Still, this flexibility introduced complexity. Monitoring asynchronous chains demanded new observability strategies. Guaranteeing event order and handling duplicates took serious effort.

Ideal For:

• Decoupled services with asynchronous workflows

• High scalability, fault tolerance scenarios

for example: Below diagram shows user signup publishes events asynchronously, triggering multiple independent services without direct coupling.

// Event-driven: Publishing an Event
on userSignup(userId):
  kafka.publish("user.signup", { userId: userId })

// Event-driven: Subscribing to an Event
kafka.subscribe("user.signup", event => {
  sendWelcomeEmail(event.userId);
  initiateBilling(event.userId);
})

---

REST: Simplicity Still Matters

Despite everything, REST remained useful. Public-facing APIs, simple CRUD operations, and straightforward integrations still benefited greatly from REST's clarity.

We didn’t abandon REST, we just became smarter about when and how to use it.

Ideal For:

• Public-facing APIs with clear documentation

• Simple, predictable data exchanges

Conclusion: Architecture Defines Your Company

Moving beyond REST didn't mean discarding it entirely. it meant carefully complementing it. Every API strategy reflects your organization's priorities, team structures, and scaling requirements.

Ultimately, choosing between REST, GraphQL, gRPC, and event-driven models isn't about selecting the best paradigm universally, but rather identifying the ideal tool for each unique situation.

Our journey began with REST, but it evolved as we recognized our growing needs. What's yours?