When building high-performance microservices in Go, one question inevitably comes up: Should you use REST or gRPC? This isn’t just an architectural debate it directly impacts latency, throughput, infrastructure cost, and scalability. In this post, we’ll break down REST vs gRPC performance using real benchmarks, practical Go examples, and production insights. Before diving into benchmarks, it’s important to understand why performance differs. Uses HTTP/1.1 (typically) Data format: JSON (text-based) Stateless, resource-oriented Uses HTTP/2 Data format: Protocol Buffers (binary) Supports streaming (bi-directional) Binary serialization is more compact and faster to parse HTTP/2 enables multiplexing multiple requests over a single connection Reduced payload size = faster network transfer ⚙️ Benchmark Setup (Go) Reference repository: 👉 https://github.com/chimanjain/go-rest-grpc-bencmark This project benchmarks: REST API (JSON over HTTP) gRPC API (Protobuf over HTTP/2) Concurrent clients Small to medium payload sizes High request volume Controlled environment for fair comparison Across benchmarks (including the referenced repo), a few consistent patterns emerge. gRPC shows: Lower latency Higher throughput Better CPU efficiency REST: Performs well at low scale Degrades faster under heavy load due to parsing and connection overhead Factor REST gRPC Serialization JSON (text) Protobuf (binary) Transport HTTP/1.1 HTTP/2 Payload Size Larger Smaller Parsing Cost Higher Lower Streaming Limited Native package main import ( "encoding/json" "net/http" ) type User struct { ID string `json:"id"` Name string `json:"name"` } func getUser(w http.ResponseWriter, r *http.Request) { user := User{ID: "1", Name: "John"} w.Header().Set("Content-Type", "application/json") json.NewEncoder(w).Encode(user) } package main import ( "context" pb "example/proto" ) type server struct { pb.UnimplementedUserServiceServer } func (s *server) GetUser(ctx context.Context, req *pb.UserRequest) (*pb.UserResponse, error) { return &pb.UserResponse{ Id: "1", Name: "John", }, nil } REST: manual serialization using encoding/json gRPC: strongly typed, auto-generated code via .proto files gRPC typically achieves lower p99 latency Especially noticeable with: High concurrency Small payloads Reason: smaller payloads + faster serialization gRPC supports more requests per second HTTP/2 multiplexing reduces connection overhead JSON parsing is CPU-intensive Protobuf significantly reduces CPU overhead Protobuf messages are smaller than JSON Less bandwidth usage leads to faster transfers Despite the performance gap, REST is still a solid choice in many scenarios: Low to moderate traffic Large payloads (compression reduces differences) Public APIs and browser-based clients Faster development and easier debugging In many real-world systems, the performance difference is not critical. Internal microservices communication High-throughput or low-latency systems Real-time streaming (e.g., chat, telemetry) Strong contract enforcement is needed Building public-facing APIs Browser compatibility is required Simplicity and ecosystem support matter Use gRPC internally and REST externally This gives you performance where it matters and compatibility where it’s needed. gRPC is faster by design due to: HTTP/2 Protobuf serialization Efficient connection handling REST is: Simpler More widely supported “Fast enough” for many applications Performance decisions should always be context-driven. Building high-scale backend systems? → gRPC Building public APIs? → REST The best architecture often combines both. https://github.com/chimanjain/go-rest-grpc-bencmark https://grpc.io/docs/what-is-grpc/introduction/ https://pkg.go.dev/net/http https://developers.google.com/protocol-buffers 💬 If you’ve run your own benchmarks in Go, feel free to share your results!