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Quix Streams vs Timely Dataflow

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

Quix Streams

Free plan LinuxSelf-hosted

Choose Quix Streams if you are building Kafka-based real-time applications in Python and want stateful processing, windowed aggregations or exactly-once guarantees. Look elsewhere if you need SQL processing or a Schema Registry offered and configured directly through Quix Cloud.

Visit Quix Streams

Timely Dataflow

Paid APISelf-hosted

Timely Dataflow offers a Rust model for streaming computation that spans local threads and cluster execution. Its documentation caveat is worth noting when getting started or adapting examples.

Visit Timely Dataflow

The facts

Quix StreamsTimely Dataflow
Free planYesNot published
Open sourceNot publishedNot published
Runs onLinux, Self-hostedAPI, Self-hosted
Lowest paid planFree or on requestNot published
Plans published1None
MakerNot publishedNot published
Websitequix.iotimelydataflow.github.io
On stream processing software#20 of 26#24 of 26

Quix Streams: what it does well

  • Open-source Python library with no listed charge.
  • Supports stateful processing using RocksDB.
  • Offers at-least-once and exactly-once processing guarantees.
  • Supports multiple serialization formats, including Avro and Protobuf.
  • Can run locally and in Jupyter Notebook.

What to know first

  • A Kafka broker is required.
  • Quix Cloud does not offer a Schema Registry.
  • The library supports Python, not SQL processing.

Timely Dataflow: what it does well

  • Same program can run locally or across a cluster.
  • Supports unbounded streams and parallel workers.
  • Includes built-in and custom operator options.
  • Differential Dataflow adds group, join, and iteration.
  • MIT licensed and self-hosted.

What to know first

  • Documentation is described as a work in progress.
  • Some blog examples may need adjustment for current code.

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