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Apache Samza vs Kafka Streams

Both stand on stream analytics software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.

Apache Samza

Free plan APILinuxSelf-hosted

Choose Apache Samza if you need a free, self-hosted framework for real-time stream processing with state stores, multiple APIs, and built-in integrations. Look elsewhere if you need a binary release or a processing guarantee beyond at least once.

Visit Apache Samza

Kafka Streams

Free plan LinuxMacSelf-hosted+1

Kafka Streams provides stateful processing tools for applications built around Kafka, with deployment options from one machine to distributed workloads. Teams should account for its Java and Scala support and lack of formal commercial support.

Visit Kafka Streams

The facts

Apache SamzaKafka Streams
Free planYesYes
Open sourceNot publishedNot published
Runs onAPI, Linux, Self-hostedLinux, Mac, Self-hosted, Windows
Lowest paid planFree or on requestFree or on request
Plans published11
MakerNot publishedNot published
Websitesamza.apache.orgkafka.apache.org
On stream analytics software#8 of 26#12 of 26

Apache Samza: what it does well

  • Free plan with open-source distribution.
  • Supports both stateful and stateless stream processing.
  • Offers Streams, Task, SQL, and Beam APIs.
  • Integrates with Kafka, Kinesis, Azure Event Hubs, Elasticsearch, and Hadoop.
  • Supports YARN, Kubernetes, or standalone deployment.

What to know first

  • Self-hosted deployment requires users to run Samza.
  • The download page says no binary release is available.
  • Python and Go support for Beam is work in progress.
  • Processing guarantee is at least once.

Kafka Streams: what it does well

  • Free client library under Apache License 2.0.
  • Supports event-time processing and windowing.
  • Provides exactly-once processing semantics.
  • No separate processing cluster is required.
  • Supports fault-tolerant local state.

What to know first

  • No formal or commercial support from the Apache Software Foundation.
  • Applications require Kafka clusters for input and output data.
  • Supported application languages listed are Java and Scala.

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