Kompressor

0.5.0indexed

High-performance compression toolkit offering ZStandard (zstd) with SliceTransform streaming API, ByteArray transforms, kotlinx-io piping, native backends via NativeBuilds, and more algorithms planned.

AndroidJSJVMNativeWasm·ensody/Kompressor

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Kompressor - Kotlin Multiplatform compression algorithms

This project provides compression algorithms for Kotlin Multiplatform.

The underlying native libraries are provided by the NativeBuilds project.

Supported platforms

Android
JVM
All native (iOS, macOS, Linux, Windows, tvOS, watchOS)

Supported algorithms

zstd/ZStandard
deflate (zlib & raw)
gzip
brotli
...more planned... (lz4, snappy, bzip2, bzip3)

Installation

Add the package to your build.gradle.kts's dependencies {}:

IMPORTANT: One reason why you should explicitly define the NativeBuilds library version is that dependabot and other automatic update tools might otherwise not suggest updates of native libraries. Since these are usually written in C/C++ or possibly unsafe Rust, you really want to stay up to date with the latest security fixes.

Also, make sure you've integrated the Maven Central repo, e.g. in your root build.gradle.kts:

subprojects {
    repositories {
        // ...
        mavenCentral()
        // ...
    }
}

Example: zstd

Every compression algorithm implements the SliceTransform interface.

If the data fits in RAM you can simply call the .transform(ByteArray) extension function:

val testData: ByteArray = Random.nextBytes(128 * 1024 + 3)
val compressed: ByteArray = ZstdCompressor(compressionLevel = 3).transform(testData)
val decompressed: ByteArray = ZstdDecompressor().transform(compressed)
assertContentEquals(testData, decompressed)

Normally, you'll want to stream the data, so even large inputs fit in RAM. While SliceTransform provides a low-level API for this, let's better use kotlinx-io:

val source: Source = ...
val sink: Sink = ...
source.pipe(ZstdCompressor(compressionLevel = 3)).buffered().use { it.transferTo(sink) }

Or for decompression:

source.pipe(ZstdDecompressor()).buffered().use { it.transferTo(sink) }

You can also build a pipe with a sink:

ZstdDecompressor().pipe(sink).buffered().use { decompressor ->
    source.transferTo(decompressor)
}

Example: zstd with Ktor

val client = HttpClient(CIO) {
    install(ContentEncoding) {
        customEncoder(ZstdContentEncoder(compressionLevel = 1), 1.0f)
    }
}

License

Copyright 2026 Ensody GmbH, Waldemar Kornewald

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance  the License.
You may obtain a copy of the License at

   http:

Unless   applicable law  agreed to  writing, software
distributed under the License  distributed  an  BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express  implied.
See the License  the specific language governing permissions 
limitations under the License.

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Installation

Add the package to your build.gradle.kts's dependencies {}:

Also, make sure you've integrated the Maven Central repo, e.g. in your root build.gradle.kts:

subprojects { repositories { // ... mavenCentral() // ... } }

Example: zstd

Every compression algorithm implements the SliceTransform interface.

If the data fits in RAM you can simply call the .transform(ByteArray) extension function:

val testData: ByteArray = Random.nextBytes(128 * 1024 + 3) val compressed: ByteArray = ZstdCompressor(compressionLevel = 3).transform(testData) val decompressed: ByteArray = ZstdDecompressor().transform(compressed) assertContentEquals(testData, decompressed)

Normally, you'll want to stream the data, so even large inputs fit in RAM. While SliceTransform provides a low-level API for this, let's better use kotlinx-io:

val source: Source = ... val sink: Sink = ... source.pipe(ZstdCompressor(compressionLevel = 3)).buffered().use { it.transferTo(sink) }

Or for decompression:

source.pipe(ZstdDecompressor()).buffered().use { it.transferTo(sink) }

You can also build a pipe with a sink:

ZstdDecompressor().pipe(sink).buffered().use { decompressor -> source.transferTo(decompressor) }

License

Copyright 2026 Ensody GmbH, Waldemar Kornewald Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance the License. You may obtain a copy of the License at http: Unless applicable law agreed to writing, software distributed under the License distributed an BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express implied. See the License the specific language governing permissions limitations under the License.