I Replaced My REST API with GraphQL — Here’s What Broke

Source: Dev.to

Motivation for Switching

• Too many REST endpoints for related data
• Frontend constantly asking for response‑shape changes
• Over‑fetching on mobile
• Under‑fetching requiring multiple API calls
• Faster feature experimentation

GraphQL promised

• Single endpoint
• Strong typing
• Precise data fetching
• Self‑documenting schema
• Better developer experience

Technically it delivered, but it introduced new complexity in places I wasn’t prepared for.

What Broke

N+1 Queries

# Example GraphQL query (simplified)
query {
  users {
    id
    name
    posts {
      id
      title
    }
  }
}

• Looks elegant, but under the hood it can become 1 query to fetch users + N additional queries to fetch posts per user.
• Performance dropped quickly.

Fixes applied

• Implemented DataLoader for batched database queries
• Added per‑request caching
• Refactored resolvers

Caching Challenges

We had to:

• Generate query‑based cache keys
• Use persisted queries
• Add a Redis layer for caching
• Manually handle invalidation

Caching shifted from infrastructure‑level to application‑level logic—a major architectural shift.

Error Handling & HTTP Semantics

• REST: 200 = success, 404 = not found, 500 = server error.
• GraphQL: Most responses return 200 even on failure; errors are embedded in the response body.

This created new frontend complexity:

• Handling partial success
• Detecting resolver failures
• Debugging deeply nested errors

Monitoring systems that relied on status codes became less useful.

Performance & Security Risks

• Deeply nested queries
• Expensive joins triggered accidentally
• Query‑depth attacks
• Introspection exposed in production
• Resource‑heavy queries from mobile clients

One badly written query could hit multiple relational layers and spike database load.

Guardrails We Added

• Query depth limiting
• Complexity scoring
• Rate limiting
• Disabled introspection in production
• Strict resolver validation
• Timeout thresholds

Observability Overhaul

REST Logging

• Each route logs separately → easy to identify slow endpoints.

GraphQL Logging

• Everything is a POST to /graphql.
• Implemented:
  • Operation name logging
  • Resolver‑level timing
  • Query tracing
  • APM integration
  • Custom performance dashboards

Without this visibility, debugging performance issues became painful.

Benefits Gained

• Frontend speed increased (reduced over‑fetching)
• Better developer experience (stronger type contracts)

When GraphQL Makes Sense

Choose GraphQL if

• You support multiple clients (web, mobile, admin)
• Your data model is highly relational
• Frontend needs flexibility
• Your team understands performance trade‑offs
• You’re ready to invest in observability

Stick with REST if

• Your API is relatively simple
• Caching is critical
• You rely heavily on HTTP semantics
• Your team prefers straightforward debugging
• You don’t need flexible querying

Sometimes boring technology is the most scalable decision.

Trade‑offs Overview

Neither approach is objectively superior; they solve different problems.

Final Thoughts

If you’re considering replacing REST with GraphQL, don’t do it because it’s trendy. Do it because:

• Your frontend genuinely benefits from flexibility
• You understand resolver performance
• You’re ready to build guardrails
• You have monitoring in place

GraphQL is powerful, but power without constraints becomes chaos.

We applied many of these lessons while refining parts of our own platform architecture at Exact Solution, especially around query‑complexity control and caching strategy. The migration forced us to think much deeper about performance boundaries than REST ever did.

---

If you’ve migrated from REST to GraphQL, what broke for you? Was it worth it? Let’s discuss below.