akhq VS kestra

Download docker-compose from github - https://github.com/tchiotludo/akhq. Launch docker-compose:

You also have https://akhq.io/

This may help as well https://akhq.io/

akHQ - https://github.com/tchiotludo/akhq

AKHQ

The project start as a side project (yet another side project I do the night and weekend) but was quickly promoted and used in a French Big Retail Company.

This one trust on the project and decide to go production with Kestra. So they decide to inject some resource in order to develop some features that need and that is missing.

But basically, not so much people for now. We are trying to start a community around the product and started to communicate around the product since few weeks only, I hope community will follow us! And I hope to succeed like on my other open source project: https://github.com/tchiotludo/akhq

Kestra's communication is asynchronous and based on a queuing mechanism. It leverages the Micronaut framework and offers two runners: one that uses a database (JDBC) for both the message queue and resource storage, and another that uses Kafka as the message queue and Elasticsearch as the resource storage. The platform is fully extensible and plugin-based, providing a rich set of plugins for various workflow tasks, triggers, and data storage options. For those interested, the GitHub repository is available here: https://github.com/kestra-io/kestra

For everyone wondering https://github.com/kestra-io/kestra/discussions/468

If you need any guidance with your Snowflake deployment, our experts at Kestra would love to hear from you. Let us know if you would like us to add more plugins to the list. Or start building your custom Kestra plugin today and send it our way. We always welcome contributions!

But I totally agree that a large static dag is not appropriate in the actual data world with data mesh and domain responsibility.

[0] https://github.com/kestra-io/kestra

- We have plans to add another option that will replace both dependencies with jdbc (https://github.com/kestra-io/kestra/pull/368), is theses dependencies more comfortable for you?

With Kestra's innate flexibility, and many integrations, you are not locked into the choice of one ingestion method or the other. Complex workflows can be developed, whether in parallel or sequentially, to deliver both ELT and ETL processes. Simple descriptive yaml is used to connect plugins, and to create flows. Because workflows created in Kestra are represented visually, and issues can be seen in relation to individual tasks, there is no need to fear complexity. Trouble can be traced to its source in an instant, allowing you to try new things and come up with a new solution without fear. Give it a try, and let us know what you come up with!

Kestra is an orchestration and scheduling platform that is designed to simplify the building, running, scheduling, and monitoring of complex data pipelines. Data pipelines can be built in real-time, no matter how complex the workflow, and can connect to multiple resources as needed (including Debezium).