Kotlin vs Python for Backend: What to Choose in 2025?

Kotlin vs Python: what to choose for backend?

Choosing a programming language for backend is one of the key decisions that affects development speed, performance, and project scalability. Python has long been a favorite due to its simplicity and huge community. However, in recent years Kotlin has been rapidly gaining momentum, especially in the enterprise segment. In this article, we will use examples to examine why Kotlin is worth considering for modern backend development, and in which cases Python still remains the best choice.

1. Performance and execution speed

When it comes to the speed of a server application, Kotlin has a significant advantage. Kotlin compiles to JVM bytecode and runs on the Java Virtual Machine (JVM) with a powerful JIT compiler. This provides a 2-5 times performance boost compared to interpreted Python.

Example: REST API in Kotlin (Ktor)

import io.ktor.server.engine.*import io.ktor.server.netty.*import io.ktor.server.routing.*import io.ktor.server.response.*

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

This code launches an HTTP server with minimal memory consumption. Thanks to coroutines, Kotlin easily handles thousands of concurrent requests without blocking threads, which is critical for high-load systems.

Python (for example, FastAPI or Django) can also work asynchronously, but its GIL (Global Interpreter Lock) limits thread execution. For CPU-intensive tasks, Python often requires additional libraries (NumPy, multiprocessing), whereas Kotlin handles them natively.

2. Type safety and code reliability

One of the main problems with Python is the lack of strict typing. You can pass a string where a number is expected, and the error will only appear at runtime. In large projects, this leads to hours of debugging and unexpected crashes in production.

Kotlin is a statically typed language with a powerful type inference system. The compiler checks code correctness at build time, preventing a whole class of errors.

Example: handling nullable values

fun getUserName(id: Int): String? {    // returns null if user is not found    return db.findUser(id)?.name}

fun printUserName(id: Int) {    val name = getUserName(id)    // The compiler will force you to handle null:    println(name ?: "User not found")}

In Python, you would have to rely on conditional statements and hope that you haven't forgotten to check for None. In Kotlin, the type system itself reminds you about potential null values, making the code more reliable.

3. Ecosystem and tools for backend

Python has a huge ecosystem: Django, Flask, FastAPI, SQLAlchemy — these are just the tip of the iceberg. However, many of these frameworks have limitations in terms of performance and scalability.

Kotlin, on the other hand, is fully compatible with the Java ecosystem. This means access to tens of thousands of mature libraries and frameworks:

• Spring Boot — the most popular framework for enterprise backend on JVM. Kotlin is natively supported in Spring.
• Ktor — a lightweight asynchronous framework from JetBrains, ideal for microservices.
• Exposed — an ORM for Kotlin with type-safe DSL queries.
• Vert.x — a tool for reactive applications.

Example: working with a database using Exposed

import org.jetbrains.exposed.sql.*import org.jetbrains.exposed.sql.transactions.transaction

object Users : Table() {    val id = integer("id").autoIncrement()    val name = varchar