Camunda Platform allows for visual demonstration and presentation of business process flows. The flexible Java-based option was a big win for us and allows for the integration of microservices very quickly. Camunda Platform is very stable, with a free open-source version that is very good. The automation is great.
Camunda Platform can be challenging regarding the initial setup, though, and it seems to take a long time for completed workflows to be implemented. The learning curve for this Camunda Platform can be pretty steep. A mobile app would be a welcome enhancement. Process interfaces between diagrams could be improved and better template options would be welcomed.
Apache Airflow integrates well with other pipelines and solutions. We like the direct support we get from Python using Apache Airflow. This makes work and automation much easier. Apache Airflow handles complex workflows and coordination of tasks easily. We can use it to manage large-scale data processing workloads using DAG, which is a core component of Apache Airflow.
Using Apache Airflow is okay, but managing it has its challenges. We would expect better scaling, especially since it is on the cloud. Apache Airflow is also not a great solution for those who are not tech-savvy. (It is not for business-end users.)
Conclusion:
Both of these solutions require some level of technical expertise to implement and manage, which is something to keep in mind.
We felt Apache Airflow offered better integration with the solutions we are currently using. We have a solid relationship currently with Python and are using many solutions that make Apache Airflow the best choice for us.
We performed a comparison between Apache Airflow and Camunda Platform based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Ease of Deployment: Most Apache Airflow users say the initial setup is complex. Some Camunda Platform users say the initial setup is straightforward, while others feel it is complex.
Features: Users of both products are happy with their stability and integration capabilities. Apache Airflow users...
Camunda Platform allows for visual demonstration and presentation of business process flows. The flexible Java-based option was a big win for us and allows for the integration of microservices very quickly. Camunda Platform is very stable, with a free open-source version that is very good. The automation is great.
Camunda Platform can be challenging regarding the initial setup, though, and it seems to take a long time for completed workflows to be implemented. The learning curve for this Camunda Platform can be pretty steep. A mobile app would be a welcome enhancement. Process interfaces between diagrams could be improved and better template options would be welcomed.
Apache Airflow integrates well with other pipelines and solutions. We like the direct support we get from Python using Apache Airflow. This makes work and automation much easier. Apache Airflow handles complex workflows and coordination of tasks easily. We can use it to manage large-scale data processing workloads using DAG, which is a core component of Apache Airflow.
Using Apache Airflow is okay, but managing it has its challenges. We would expect better scaling, especially since it is on the cloud. Apache Airflow is also not a great solution for those who are not tech-savvy. (It is not for business-end users.)
Conclusion:
Both of these solutions require some level of technical expertise to implement and manage, which is something to keep in mind.
We felt Apache Airflow offered better integration with the solutions we are currently using. We have a solid relationship currently with Python and are using many solutions that make Apache Airflow the best choice for us.