Go vs Spring Boot: After 2 years with both in production

I've worked 2 years with microservices in Go and Spring Boot at the same company, same team, same infrastructure. No "I did a hello world and Go is 1000x better". Here's the real data.

Mental Model

The fundamental difference isn't the language, it's the philosophy:

Go forces you to be explicit: if something can fail, return error. If you need concurrency, use goroutines. Everything is in plain sight.

Spring Boot abstracts for you: @Transactional handles transactions, @Async converts methods to async, Spring Security "just works". Until it doesn't.

Under the Hood: Where each one wins

Startup and memory

For serverless (Lambda, Cloud Functions), Go clearly wins. Cold starts of 100ms vs 4 seconds is the difference between acceptable UX and unacceptable.

For Kubernetes with many pods, the memory difference matters: 8MB vs 180MB means 20x more pods per node.

Performance under load

Benchmark: 10k requests, 100 concurrent connections
Endpoint: GET /api/users/:id (PostgreSQL query)

              | Go (net/http) | Spring WebMVC | Spring WebFlux
--------------+---------------+---------------+----------------
Requests/sec  | 45,000        | 12,000        | 38,000
p50 latency   | 2.1ms         | 8.2ms         | 2.6ms
p99 latency   | 4.8ms         | 45ms          | 12ms
CPU usage     | 35%           | 85%           | 60%

Concurrency: goroutines vs threads

Go:

func processUsers(ids []int) []User {
    results := make(chan User, len(ids))
    var wg sync.WaitGroup
 
    for _, id := range ids {
        wg.Add(1)
        go func(id int) {
            defer wg.Done()
            user := fetchUser(id)  // Blocking, but in goroutine
            results <- user
        }(id)
    }
 
    wg.Wait()
    close(results)
 
    var users []User
    for u := range results {
        users = append(users, u)
    }
    return users
}

Spring Boot (WebFlux):

public Flux<User> processUsers(List<Integer> ids) {
    return Flux.fromIterable(ids)
        .flatMap(id -> webClient.get()
            .uri("/users/{id}", id)
            .retrieve()
            .bodyToMono(User.class))
        .collectList()
        .flatMapMany(Flux::fromIterable);
}

Go code is longer but you can debug it with a normal stack trace. In WebFlux, when something fails in the middle of a reactive chain, good luck.

Error handling

Go:

user, err := db.GetUser(id)
if err != nil {
    if errors.Is(err, sql.ErrNoRows) {
        return nil, ErrUserNotFound
    }
    return nil, fmt.Errorf("fetching user %d: %w", id, err)
}

Spring:

try {
    return userRepository.findById(id)
        .orElseThrow(() -> new UserNotFoundException(id));
} catch (DataAccessException e) {
    throw new ServiceException("Error fetching user", e);
}

Go's approach is verbose but explicit. In Spring, you need to know what exceptions each layer can throw (spoiler: documentation is never complete).

Real example: Same service in both

Payment processing API

Go (395 total lines):

// main.go - Entry point
func main() {
    cfg := config.Load()
    db := database.Connect(cfg.DatabaseURL)
    defer db.Close()
 
    paymentService := payment.NewService(db, stripe.NewClient(cfg.StripeKey))
    handler := api.NewHandler(paymentService)
 
    mux := http.NewServeMux()
    mux.HandleFunc("POST /payments", handler.CreatePayment)
    mux.HandleFunc("GET /payments/{id}", handler.GetPayment)
 
    log.Printf("Starting server on :8080")
    log.Fatal(http.ListenAndServe(":8080", mux))
}

Spring Boot (project structure):

src/main/java/com/example/payments/
├── PaymentsApplication.java
├── config/
│   ├── StripeConfig.java
│   └── SecurityConfig.java
├── controller/
│   └── PaymentController.java
├── service/
│   └── PaymentService.java
├── repository/
│   └── PaymentRepository.java
├── model/
│   ├── Payment.java
│   └── PaymentDTO.java
├── exception/
│   ├── PaymentNotFoundException.java
│   └── GlobalExceptionHandler.java
└── mapper/
    └── PaymentMapper.java

11 Java files vs 4 Go files for the same functionality.

When to choose each one

Choose Go when:

• Serverless/Lambda: Cold starts matter
• CLI tools: Static binary, trivial distribution
• Infrastructure: Proxies, load balancers, DevOps tools
• High concurrency: Thousands of simultaneous connections
• Limited resources: Edge computing, IoT

Choose Spring Boot when:

• Java ecosystem: Integration with existing Java libraries
• Enterprise features: OAuth2, SAML, AD integration
• Java team: Learning curve vs productivity
• Complex transactions: Spring Transaction Management is very mature
• Powerful ORM: JPA/Hibernate for complex schemas

Gotchas of each stack

Go

1. Repetitive error handling: if err != nil everywhere
2. No powerful generics: Until Go 1.18, copy/paste for each type
3. Manual dependency injection: No magic, but also no magic
4. Immature ORM: GORM has its quirks, sqlx is more raw

Spring Boot

1. Startup time: 4+ seconds in development is frustrating
2. Excessive magic: When @Transactional doesn't do what you expect
3. ClassNotFoundException hell: Dependency version conflicts
4. Memory footprint: 300MB+ for a CRUD

TL;DR Checklist

My personal choice: Go for new services I control, Spring Boot when integrating with existing Java ecosystem. There's no universal answer.

Want me to go deeper into WebFlux vs goroutines or how to gradually migrate from Spring to Go?