Add Dependency:

In your Kotlin project, you'll need to add the MongoDB driver dependency to your build.gradle (for Gradle) or build.gradle.kts (for Kotlin DSL) file. Here's an example for Gradle:
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implementation 'org.mongodb:mongodb-driver-sync:4.2.3'
Create a MongoDB Connection:

Initialize a MongoDB client to connect to your MongoDB server. Replace localhost and 27017 with the appropriate MongoDB server address and port.
kotlin
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import com.mongodb.client.MongoClients

val client = MongoClients.create("mongodb://localhost:27017")
Select a Database:

Choose the MongoDB database you want to work with.
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val database = client.getDatabase("your_database_name")
Select a Collection:

Choose the collection within the database you want to query.
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val collection = database.getCollection("your_collection_name")
Perform Queries:

You can now perform various queries on the MongoDB collection. Here are some examples:

Find documents:

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import org.bson.Document

val query = Document("field_name", "value_to_match")
val cursor = collection.find(query).iterator()

while (cursor.hasNext()) {
    val document = cursor.next()
    // Process the document here
}
Insert a document:

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val document = Document("field1", "value1")
collection.insertOne(document)
Update documents:

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val filter = Document("field_name", "value_to_match")
val update = Document("\$set", Document("field_to_update", "new_value"))
collection.updateOne(filter, update)
Delete documents:

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val filter = Document("field_name", "value_to_match")
collection.deleteOne(filter)
Close the Connection:

Don't forget to close the MongoDB client when you're done with it to release resources.
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client.close()
Now, regarding the key differences between Kotlin and Python:

Static vs. Dynamic Typing:

Kotlin is statically typed, which means you must declare variable types at compile time. Python, on the other hand, is dynamically typed, allowing variables to change types at runtime.
Syntax:

Kotlin has a more concise and expressive syntax compared to Python. It places a strong emphasis on type safety and null safety.
Performance:

Kotlin generally offers better performance due to its statically typed nature, while Python tends to be slower because of its dynamic typing.
Concurrency and Parallelism:

Kotlin provides native support for coroutines, making it easier to write asynchronous and concurrent code. Python has libraries like asyncio, but it doesn't have native support for coroutines.
Ecosystem:

Python has a larger and more mature ecosystem with extensive libraries and frameworks for various domains, including web development, data science, and machine learning. Kotlin's ecosystem, while growing, is not as extensive.
Community and Adoption:

Python has been around for a long time and has a massive community and widespread adoption in various industries. Kotlin is relatively newer but gaining popularity, especially in Android app development.
Platform:

Python is often used for scripting, web development, and data analysis. Kotlin is versatile but is prominently used for Android app development and backend development.
Null Safety:

Kotlin has built-in null safety features, reducing null pointer exceptions, which are common in many programming languages. Python does not have this feature by default.
Both languages have their strengths and are suitable for different use cases. The choice between Kotlin and Python depends on your project requirements, personal preferences, and the domain in which you're working.
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