Ktor vs. Spring Boot: 5 Key Differences for Kotlin Devs

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Javarevisited

10 min readJul 25, 2024

Hypothetically speaking, why would a Kotlin developer need Ktor if they could use Spring Boot, which is popular worldwide and they are very used to it? Although Ktor is flexible and lightweight for building asynchronous server-side web apps with fast start-up times and other cool features, they are accustomed to Spring Boot. So why should they make the move?

What I realized is that Comparisons against an established tool in the market are not entirely fair. And still, I can ask the same question: why should I choose Kotlin over Java?

Still, I decided to ask experienced Java/Kotlin developers about the benefits of using Ktor with Kotlin applications and create some sort of comparison.

In this article, we will explore the key differences between Ktor and Spring Boot for Kotlin developers based on the experience of various developers.

Disclaimer: If you feel there is some bias towards one framework or another, it wasn’t the intention.

The comparison in this blog criteria is based on the following 5 parameters:

Performance
Async work/threading
Ecosystem
Developer Experience
Observability Capabilities

1. Performance

Snapiness

Ktor is built purely using Kotlin, which has a more concise syntax than Java. This design is simple, making it easier to write and maintain code.

fun Application.module() {
  routing {
    get("/greet") {
      call.respondText("Hello, Ktor!")
    }
  }
}

Ktor is built to be asynchronous from the ground up, all thanks to Kotlin’s coroutines. These features will make Ktor a good developer experience for developers looking for a lightweight framework that is modern and suited for modern architecture.

Spring Boot might present a steep learning curve due to its “bloated” ecosystem, which can be overwhelming for beginners; this problem can be mitigated by its extensive documentation and community support.

@SpringBootApplication
public class MySpringBootApplication {
    public static void main(String[] args) {
        SpringApplication.run(MySpringBootApplication.class, args);
    }
}
@RestController
@RequestMapping("/greet")
public class GreetingController {
    @GetMapping
    public String greet() {
        return "Hello, Spring Boot!";
    }
}

Due to Spring Boot’s strong community support, it is a go-to for enterprise-level applications that need extensive integrations. Ktor, while boasting of its simplicity, may not offer the same level of integration due to its smaller ecosystem.

Dependency injection

I recommend Kolin for Dependency Injection. Works well with Ktor.

Koin (for DI) is great to use with Ktor and can be used even for small projects or microservices.

My team moved from spring to targeted libraries about five years ago and hasn’t looked back. We don’t use Ktor, but other teams do, and the reasoning is the same.

Easier upgrades since there aren’t interdependencies
There is no “magic”; the code you write is the code that is run.
The dependency tree is about 1/3rd the size of the same functionality
Startup time is instantaneous
Reasoning about any complex application is significantly easier as all the code being run is right there.

fun main() {
    startKoin {
        modules(appModule)
    }
    embeddedServer(Netty, port = 8080) {
        routing {
            get("/do-something") {
                val myService = get<MyService>()
                myService.doSomething()
                call.respond(HttpStatusCode.OK)
            }
        }
    }.start(wait = true)
}

Spring Boot’s DI implementation is quite different and opinionated. Yes, the magic of auto-wiring in Spring Boot is cool; however, I have discovered that it has the potential to increase application loading times due to unnecessary dependencies.

GraalVM

Given that Ktor is a lightweight framework for developing asynchronous servers and microservices, it’s reasonable to assume that it could see improvements from GraalVM’s native-image tool, like Spring Boot, resulting in quicker startup times and possibly smaller deployment sizes.

Spring Boot’s memory footprint and startup time can be reduced to an extent because of GraalVM. However, your memory footprint using GraalVM on a Spring Boot project can not be compared to what you’ll get with Ktor. Memory footprint is something that is inconsequential when it is not a cloud-native project.

2. Async work/threading

Coroutines / Virtual Threads

Ktor fully uses Coroutines, which is good for highly concurrent code, event-based systems, and structured concurrency and cancellations.

Coroutines address the issues surrounding:

Effortlessly writing parallel, non-blocking code without errors (structured concurrency)
Nesting callbacks to switch between threads can be replaced with synchronous code, resulting in code that is easier to read, write, and understand. A frequent scenario involves code needing to switch between performing UI tasks on a main thread, which cannot be interrupted, and carrying out blocking tasks on IO threads.

fun main() {
    embeddedServer(CIO, port = 8080, host = "0.0.0.0", module = Application::module)
        .start(wait = true)
}
fun Application.module() {
    routing {
        get("/greet") {
            call.respondText("Hello, World!", ContentType.Text.Plain)
        }
        get("/async-greet") {
            // Launch a coroutine to simulate an asynchronous operation
            val greeting = asyncGreet()
            call.respondText(greeting, ContentType.Text.Plain)
        }
    }
}
suspend fun asyncGreet(): String = withContext(Dispatchers.Default) {
    delay(1000) // Simulate a long-running task
    "Hello from Coroutine!"
}

Since Ktor has coroutines, which takes care of asynchronous task at the language level, virtual threads is an added advantage at the JVM level.

Spring Boot can leverage Virtual threads to tackle the problem of IO tasks, which typically block an OS thread throughout its execution. This approach fundamentally reduces the resources required for handling blocking, synchronous tasks, especially when dealing with extensive operations. Virtual threads operate at the JVM level, so they can be integrated seamlessly into a Spring Boot project.

server:
 port: 8080
spring:
 application:
   name: digma-demo
 threads:
   virtual:
     enabled: true
@RestController
@RequestMapping("api/v1/")
public class AppController {
   @Value("${spring.application.name}")
   private String appName;
   private final Logger LOGGER = LoggerFactory.getLogger(AppController.class);
   @GetMapping("hello")
   public String getValue(){
       LOGGER.info("Thread Info: {}", Thread.currentThread());
       String response = "Hello World from : "+ appName;
       LOGGER.info("Response: {}", response);
       return response;
   }
}

Request Response Handling

Ktor enables you to manage incoming requests and send back responses within route handlers. Different actions can be carried out while managing requests:

Get request details, like headers, cookies, etc.

routing {
    get("/") {
        val uri = call.request.uri
        call.respondText("Request uri: $uri")
    }
}

Get values from the path parameters.

get("/user/{login}") {
    if (call.parameters["login"] == "admin") {
        // ...
    }
}

Retrieve body content such as data objects, form parameters, and files.

post("/text") {
    val text = call.receiveText()
    call.respondText(text)
}

Spring Boot handles request response in a way that is not seamless, i.e, you’ll have to write your own custom request response handler and then write a custom ControllerAdvice to really fine tune what you want.

// ServiceResponse.java
@Data
public class ServiceResponse<T> {
    private T data;
    private boolean success = false;
    public ServiceResponse() {
    }
    public ServiceResponse(T data, boolean success) {
        this.data = data;
        this.success = success;
    }
    public void setData(T data, boolean success) {
        this.data = data;
        this.success = success;
    }
}

// ControllerAdvice
@Slf4j
@RestControllerAdvice
public class ControllerAdvice {
    private final MessageSource messageSource;
    public ControllerAdvice(MessageSource messageSource) {
        this.messageSource = messageSource;
    }
    @ResponseBody
    @ResponseStatus(HttpStatus.BAD_REQUEST)
    @ExceptionHandler(IllegalArgumentException.class)
    public ResponseEntity<ServiceResponse<String>> handleIllegalArgumentException(IllegalArgumentException ex) {
        return ResponseEntity.badRequest().body(new ServiceResponse<>(ex.getMessage(), false));
    }
    @ResponseBody
    @ResponseStatus(HttpStatus.BAD_REQUEST)
    @ExceptionHandler(HttpMessageNotReadableException.class)
    public ResponseEntity<ServiceResponse<String>> handleHttpMessageNotReadable(HttpMessageNotReadableException ex) {
        return ResponseEntity.badRequest().body(new ServiceResponse<>(ex.getMessage(), false));
    }
}

3. Ecosystem

Multiplatform

Ktor, in conjunction with Kotlin Multiplatform (KMP), is a library that allows you to share much of your networking code and business logic with other platforms such as Kotlin/JVM, Kotlin/Js, Android, iOS, watchOS, tvOS, macOS, Linus and Windows.

Spring Boot allows for the same functionality, but you’ll have to separate a lot of code and likely have a complex Gradle configuration.

Maintenance — dependencies and configuration

Ktor requires extensive manual configuration and setup because it does not rely on auto-configuration or component scanning. Developers must explicitly define and configure their application components, which can help them understand the application’s behavior and require more upfront effort. The lack of autoconfiguration or component scanning comes in handy when you don’t like the “magic” that takes place in Spring Boot.

Spring Boot, on the other hand, is known for auto-configuration and component scanning abilities, which significantly reduces the amount of manual configuration needed to set up a project. Developers who like a simpler project setup will find this functionality helpful.

4. Developer Experience

Boilerplate

Ktor boasts of being lightweight and not bringing any “magic” that comes with Spring Boot. Hence, to set up a project in Ktor, you’ll have to do a lot of manual configuration, leading to boilerplate code. That’s the trade-off you’ll have to deal with when working with Ktor.

fun main() {
    embeddedServer(Netty, port = 8080) {
        routing {
            get("/") {
                call.respondText("Hello, world!", ContentType.Text.Plain)
            }
        }
    }.start(wait = true)
}

Spring Boot provides numerous autoconfiguration classes that generate beans with default configurations, which come with a lot of magic, but this does not give the developer desired control from the onset.

@SpringBootApplication
public class Application {
    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }
    @RestController
    public class HelloController {
        @GetMapping("/")
        public String helloWorld() {
            return "Hello, world!";
        }
    }
}

Documentation

Ktor is relatively new, so it has a smaller ecosystem and community, resulting in fewer resources and documentation than Spring Boot.

Community

Ktor is relatively new and has a smaller community than Spring Boot. However, it is growing rapidly, especially among developers who prefer Kotlin and seek a lightweight, asynchronous solution for modern web development. Ktor’s community is active and supportive, with many online resources, including forums, blogs, and GitHub repositories.

Spring Boot has a large and robust community because it has been around for over a decade. This means there are many third-party libraries, thorough documentation, and plenty of tutorials and guides. This large support system greatly benefits developers working on enterprise applications.

5. Observability Capabilities

Ktor has a plugin called the MicrometerMetrics plugin that integrates Micrometer metrics into your Ktor server app. This allows you to select your preferred monitoring platform, such as Prometheus, JMX, Elastic, etc. Ktor has built-in metrics to track HTTP requests and JVM performance by default. You can personalise these measures or create new ones.

Spring Boot has a starter called spring-boot-starter-actuator; this dependency gives important information about application internals through endpoints such as /actuator/health, /actuator/metrics, and /actuator/env. These endpoints provide detailed metrics, health status, and environmental properties of your application.

Spring Boot integrates well with OpenTelemetry. It supports agent instrumentation and Micrometer Tracing. you can check out this blog post: https://digma.ai/couch-to-fully-observed-code-with-spring-boot-3-2-micrometer-tracing-and-digma/

I have realized that no matter the web framework of choice, it is important to have observability. Digma with Ktor or Spring Boot will help you analyze your application runtime data. It detects issues as they appear, highlights potential issues in code and helps with code change dynamic analysis and context.

Digma not only collects observability data from your personal computer but also from production — the source of truth. Digma can leverage Micrometer’s small footprint and the fact that it does not use reflection to collect observability data in production.

No matter the framework you choose, you will likely encounter errors that are difficult to trace or reproduce in a test environment. Using Digma with Ktor or Spring Boot will help you deal with database query issues and bottlenecks buried deep in your code and fix any scaling issues that you might encounter.

Observability plays an important role in the software development lifecycle across development, test, staging, and production stages. It can reveal crucial elements of your application’s behavior, pinpoint problems, and enhance your code. Enabling observability with Digma for your Ktor or Spring Boot application will give you helpful insights.

Conclusion

To round up, both frameworks offer significant benefits and are best suited for different use cases. Ktor offers a fresh take on web development akin to Spring Boot, and it appeals to those who want a web framework that is lightweight (not bloated), explicit, fast, and has a fast startup time. Meanwhile, Spring Boot remains the tried-and-tested framework for Java developers, as it appeals to those who want a robust and established ecosystem.

Choose your web framework carefully and it should be based on the needs of your project and embrace the enjoyable experience of building robust web applications! Digma not only collects observability data from your personal computer but also from production — the source of truth. Digma can leverage Micrometer’s small footprint and the fact that it does not use reflection to collect observability data in production.

Conclusion

Choose your web framework carefully and it should be based on the needs of your project and embrace the enjoyable experience of building robust web applications! Digma supports both Ktor and Spring Boot and we love both. Try it for yourself:

Ktor vs. Spring Boot: 5 Key Differences for Kotlin Devs

1. Performance

Snapiness

Dependency injection

GraalVM

2. Async work/threading

Coroutines / Virtual Threads

Request Response Handling

3. Ecosystem

Multiplatform

Maintenance — dependencies and configuration

4. Developer Experience

Boilerplate

Documentation

Community

5. Observability Capabilities

Conclusion

Conclusion

Conclusion

Written by Nir Shafrir