There's no shortage of options for building an API in 2026 — Node, Go, FastAPI, Kotlin, Rust, all legitimate, all with passionate fans. And yet when an enterprise team plans a new API that needs to run for years and talk to a dozen older systems, Java keeps coming up.
Not nostalgia. The reasons are mostly boring and mostly about what happens after the API ships.
1. OOP Keeps Big APIs From Becoming Spaghetti
"Object-oriented programming" sounds like a first-year CS lecture — inheritance, encapsulation, polymorphism. Doesn't sound like it should matter for shipping software.
Then you're six months into an API with forty endpoints, three teams touching it, and suddenly it matters a lot.
@RestController
@RequestMapping("/api/orders")
public class OrderController {
private final OrderService orderService;
@GetMapping("/{id}")
public ResponseEntity<OrderDTO> getOrder(@PathVariable Long id) {
return ResponseEntity.ok(orderService.findById(id));
}
}
@Service
public class OrderService {
private final OrderRepository orderRepository;
public OrderDTO findById(Long id) {
Order order = orderRepository.findById(id)
.orElseThrow(() -> new OrderNotFoundException(id));
return OrderMapper.toDTO(order);
}
}
Controller → service → repository → DTO isn't a Java-exclusive pattern. But Java's type system more or less forces it. Even a team that's never had an architecture conversation ends up with this structure, because fighting it takes more effort than following it.
2. Spring Boot, Micronaut, Jakarta EE — Pick Based on What's Constraining You
Spring Boot is the default because of how many decisions it makes for you, not because it's "the best" in the abstract. Embedded server, auto-config, a starter for nearly anything. Real API — DB, validation, security — running before lunch.
@SpringBootApplication
public class ApiApplication {
public static void main(String[] args) {
SpringApplication.run(ApiApplication.class, args);
}
}
@RestController
@RequestMapping("/api/health")
public class HealthController {
@GetMapping
public Map<String, String> health() {
return Map.of("status", "UP", "timestamp", Instant.now().toString());
}
}
Micronaut gets dismissed as "Spring but smaller" and that's wrong. Compile-time DI instead of Spring's runtime reflection means fast startup and low memory. On Lambda, or with 30 small services where memory and cold-start time hit your AWS bill directly — this isn't a nice-to-have, it's the actual reason to pick it.
Jakarta EE gets called the old verbose option, and sure, it is more verbose. But when an auditor asks "show me exactly how this transaction boundary is enforced," that verbosity stops being a downside.
3. The JVM Doesn't Care Where It Runs — Worth More Than It Sounds
"Write once, run anywhere" became a punchline decades ago, fair enough.
But strip the marketing: a JVM API behaves the same in staging as production, same on your laptop as on whatever Linux distro the cloud VM happens to run. For companies with hybrid cloud + on-prem + a decade of acquired infrastructure (a lot of large companies), that consistency quietly prevents an entire category of "works on my machine" incidents. Not exciting. You don't appreciate it until you've worked somewhere without it.
4. Concurrency Got Genuinely Better — Most People Haven't Noticed
The old Java answer to high concurrency was Spring WebFlux — reactive, non-blocking, and a real mental shift for teams used to top-to-bottom blocking code. Works, but the learning curve and reactive-pipeline debugging are real costs.
Java 21 changed this with virtual threads:
@RestController
public class DataController {
@GetMapping("/api/aggregate")
public AggregateResponse getAggregateData() {
// Looks like ordinary blocking code.
// Runs on virtual threads — JVM handles concurrency.
var users = userService.fetchAll();
var orders = orderService.fetchAll();
var inventory = inventoryService.fetchAll();
return new AggregateResponse(users, orders, inventory);
}
}
⚠️ This looks completely ordinary — no
Mono, noFlux, nothing to relearn. But it gets concurrency that used to require full reactive commitment. If you've been avoiding a high-concurrency rewrite because nobody wants to learn WebFlux, look at this first.
5. The Security Stuff That's Easy to Skip — Not Optional Here
Most API security incidents aren't sophisticated. Missing auth checks, no CSRF, no rate limiting, unvalidated input — the boring stuff that gets cut two days before a deadline.
@Configuration
@EnableWebSecurity
public class SecurityConfig {
@Bean
public SecurityFilterChain filterChain(HttpSecurity http) throws Exception {
return http
.authorizeHttpRequests(auth -> auth
.requestMatchers("/api/public/**").permitAll()
.requestMatchers("/api/admin/**").hasRole("ADMIN")
.anyRequest().authenticated()
)
.oauth2ResourceServer(oauth2 -> oauth2.jwt(Customizer.withDefaults()))
.csrf(csrf -> csrf.disable()) // disabled — stateless JWT API
.build();
}
}
JWT, OAuth2, RBAC — already integrated, already tested against the framework. Skipping security here means removing something, not just never adding it. That's a meaningfully different failure mode under deadline pressure.
6. Decades of Other People's Mistakes, Searchable
Something breaks at 11pm. You search the error. Someone already hit this, argued about it on Stack Overflow fifteen years ago, and one answer actually works.
Hard to overstate how much this matters when you're tired and something's on fire. Extends to the smaller frameworks too — Micronaut and Vert.x sit on the same JVM foundation and the same accumulated "oh, that error means X" knowledge.
7. Java vs. Kotlin — An Honest Take
"Java has better backward compatibility than Kotlin" gets thrown around like it settles things. It doesn't — Kotlin runs on the JVM, has full Spring Boot support, is a first-class Spring language.
What's actually true: Kotlin's null safety and data classes eliminate bug categories Java devs just live with. New project, Kotlin-comfortable team — often the better call, same ecosystem, fewer footguns.
Java's edge: bigger hiring pool, more Java-specific docs, and if you've got an existing large Java codebase, adding Kotlin means two JVM languages instead of one. Real cost even when each language is individually fine. Less "Java vs Kotlin," more "does Kotlin solve a problem this team actually has?"
So, Which One?
Depends what's constraining you — less satisfying than a ranking, more accurate.
Spring Boot covers most teams with standard REST/microservice requirements (most teams). Micronaut earns its place when memory and startup time are measurable costs. Jakarta EE makes sense when an auditor reads your code eventually.
All three: JVM consistency you don't think about, security that's built in, and an ecosystem where the hard problems are statistically already solved by someone else who was also tired at 11pm.
Building or modernizing an API and weighing Java against alternatives? At Innostax, our backend engineers work across Spring Boot, Micronaut, and Jakarta EE. Start the conversation here.
Originally published on the Innostax Engineering Blog.
Spring Boot, Micronaut, or something else for your last API? And has anyone shipped production traffic on Java 21 virtual threads — how'd it go? 👇
#java #api #springboot #backend
Top comments (0)