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dbmazz vs LinkedIn Databus

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

dbmazz

Free plan LinuxMacSelf-hosted

dbmazz provides a focused path for streaming database changes, with a one-job-per-instance limit and a defined set of stable sinks. Teams should also account for its license restriction and any separately charged BYOC support or connectivity.

Visit dbmazz

LinkedIn Databus

Free plan APISelf-hostedWeb

Databus offers change capture, replay, and bootstrap for systems that need to keep derived data aligned with primary sources. Its documented Oracle support and build dependencies are important considerations; the MySQL adapter is not a production deployment.

Visit LinkedIn Databus

The facts

dbmazzLinkedIn Databus
Free planYesYes
Open sourceNot publishedNot published
Runs onLinux, Mac, Self-hostedAPI, Self-hosted, Web
Lowest paid planFree or on requestFree or on request
Plans published21
MakerNot publishedNot published
Websitegithub.comgithub.com
On change data capture software#5 of 23#9 of 23

dbmazz: what it does well

  • Streams inserts, updates, and deletes through logical replication.
  • Stable sinks include StarRocks, PostgreSQL, and Snowflake.
  • Automatic setup can create replication slots and sink tables.
  • Self-hosted engine and BYOC plans are free.
  • CLI supports Linux and macOS on amd64 and arm64.

What to know first

  • Each instance handles one replication job.
  • S3/Iceberg is listed as roadmap, not stable.
  • BYOC support and optional PrivateLink are charged separately.
  • The license restricts offering it as a managed service.

LinkedIn Databus: what it does well

  • Free under Apache 2.0.
  • Supports replay from an arbitrary stream position.
  • Provides full-data bootstrap for catch-up.
  • Describes in-order, at-least-once delivery.
  • Supports partitioned consumption and source consistency.

What to know first

  • Build requires Oracle's ojdbc6 driver.
  • MySQL adapter is only a proof of concept.
  • Requires Gradle 1.0 or above to build.

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