ZIO Kafka is a Kafka client for ZIO. It provides a purely functional, streams-based interface to the Kafka client and integrates effortlessly with ZIO and ZIO Streams. Often zio-kafka programs have a higher throughput than programs that use the Java Kafka client directly (see section Performance below).

Apache Kafka is a distributed event streaming platform that acts as a distributed publish-subscribe messaging system. It enables us to build distributed streaming data pipelines and event-driven applications.

Kafka has a mature Java client for producing and consuming events, but it has a low-level API. ZIO Kafka is a ZIO native client for Apache Kafka. It has a high-level streaming API on top of the Java client. So we can produce and consume events using the declarative concurrency model of ZIO Streams.

In order to use this library, we need to add the following line in our build.sbt file:

libraryDependencies += "dev.zio" %% "zio-kafka"         % "2.9.0"
libraryDependencies += "dev.zio" %% "zio-kafka-testkit" % "2.9.0" % Test

Snapshots are available on Sonatype's snapshot repository https://oss.sonatype.org/content/repositories/snapshots. Browse here to find available versions.

For zio-kafka-testkit together with Scala 3, you also need to add the following to your build.sbt file:

excludeDependencies += "org.scala-lang.modules" % "scala-collection-compat_2.13"

Let's write a simple Kafka producer and consumer using ZIO Kafka with ZIO Streams. Before everything, we need a running instance of Kafka. We can do that by saving the following docker-compose script in the docker-compose.yml file and run docker-compose up:

version: '2'
services:
  zookeeper:
    image: confluentinc/cp-zookeeper:latest
    environment:
      ZOOKEEPER_CLIENT_PORT: 2181
      ZOOKEEPER_TICK_TIME: 2000
    ports:
      - 22181:2181
  
  kafka:
    image: confluentinc/cp-kafka:latest
    depends_on:
      - zookeeper
    ports:
      - 29092:29092
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://kafka:9092,PLAINTEXT_HOST://localhost:29092
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: PLAINTEXT:PLAINTEXT,PLAINTEXT_HOST:PLAINTEXT
      KAFKA_INTER_BROKER_LISTENER_NAME: PLAINTEXT
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1

Now, we can run our ZIO Kafka Streaming application:

import zio._
import zio.kafka.consumer._
import zio.kafka.producer.{Producer, ProducerSettings}
import zio.kafka.serde._
import zio.stream.ZStream

object MainApp extends ZIOAppDefault {
  val producer: ZStream[Producer, Throwable, Nothing] =
    ZStream
      .repeatZIO(Random.nextIntBetween(0, Int.MaxValue))
      .schedule(Schedule.fixed(2.seconds))
      .mapZIO { random =>
        Producer.produce[Any, Long, String](
          topic = "random",
          key = random % 4,
          value = random.toString,
          keySerializer = Serde.long,
          valueSerializer = Serde.string
        )
      }
      .drain

  val consumer: ZStream[Consumer, Throwable, Nothing] =
    Consumer
      .plainStream(Subscription.topics("random"), Serde.long, Serde.string)
      .tap(r => Console.printLine(r.value))
      .map(_.offset)
      .aggregateAsync(Consumer.offsetBatches)
      .mapZIO(_.commit)
      .drain

  def producerLayer =
    ZLayer.scoped(
      Producer.make(
        settings = ProducerSettings(List("localhost:29092"))
      )
    )

  def consumerLayer =
    ZLayer.scoped(
      Consumer.make(
        ConsumerSettings(List("localhost:29092")).withGroupId("group")
      )
    )

  override def run =
    producer.merge(consumer)
      .runDrain
      .provide(producerLayer, consumerLayer)
}

• ZIO Kafka tutorial by the ZIO-kafka team
• ZIO Kafka faster than Java Kafka by Erik van Oosten (December 2024)
• Introduction to zio-kafka by Stefanos Georgakis, Baeldung (January 2023)
• How to implement streaming microservices with ZIO 2 and Kafka by Jorge Vasquez, Scalac (June 2023)
• Zio Kafka by Knoldus Inc (January 2022)
• Writing a Simple Producer and Consumer Using ZIO Workflows by Pramod Shehan (December 2022)
• ZIO Kafka with transactions - a debugging story by Daniel Vigovszky, Ziverge (June 2022)
• Introduction to Zio-Kafka by Akash Kumar (March 2022)
• Introduction to Zio-Kafka by Khalid Ahmed, Nash Tech (March 2022)
• ZIO Kafka: A Practical Streaming Tutorial by Riccardo Cardin, Rock the JVM (August 2021)
• Using ZIO Kafka with offset storage in Postgres for transactional processing by Marek Kadek (March 2021)
• Streaming microservices with ZIO and Kafka by Aleksandar Skrbic (February 2021)
• An Introduction to ZIO Kafka by Ziverge (April 2020)

• Optimizing Data Transfer Kafka to BQ: let's use Scala to make it custom by Dario Amorosi, Adevinta (November 2024)
• Making ZIO-Kafka Safer and Faster in 2023 by Erik van Oosten (November 2023)
• ZIO Kafka with Scala: A Tutorial by Rock the JVM (August 2021)
• ZIO WORLD - ZIO Kafka by Aleksandar Skrbic (March 2020) — Aleksandar Skrbic presented ZIO Kafka, a critical library for the modern Scala developer, which hides some of the complexities of Kafka.

• Kafka BigQuery Express by Adevinta (November 2024) A production system to copy data from Kafka to BigQuery, safely and cost-effectively. (See also the video "Optimizing Data Transfer...".)
• zio-kafka-showcase by Jorge Vásquez, Example project that demonstrates how to build Kafka based microservices with Scala and ZIO
• zio-kafka-demo1 (December 2022), example consumer and producer using zio-kafka 2.0.5
• zio-kafka-example-app by Ziverge (December 2020), example application using zio-kafka 0.8.0

Here is a partial list of companies using zio-kafka in production.

Want to see your company here? Submit a PR!

• Conduktor
• KelkooGroup
• Rocker

By default, zio-kafka programs process partitions in parallel. The default java-kafka client does not provide parallel processing. Of course, there is some overhead in buffering records and distributing them to the fibers that need them. On 2024-11-23, we estimated that zio-kafka consumes faster than the java-kafka client when processing takes more than ~1.2ms per 1000 records. The precise time depends on many factors. Please see this article for more details.

If you do not care for the convenient ZStream based API that zio-kafka brings, and latency is of absolute importance, using the java based Kafka client directly is still the better choice.

Learn more on the ZIO Kafka homepage!

For the general guidelines, see ZIO contributor's guide.

See the Code of Conduct

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This library is heavily inspired and made possible by the research and implementation done in Alpakka Kafka, a library maintained by the Akka team and originally written as Reactive Kafka by SoftwareMill.

License

Copyright 2021-2024 Itamar Ravid and the zio-kafka contributors.