Apache Airflow vs. Camunda

For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.

Incentivized

Camunda Platform is well suited for scenarios where there are different stages in a business flow and the flow is driven by user action at each stage. For example placing of an order on an ecommerce platform. Depending on whether user was able to make the payment or not the workflow would go to dispatch or retry stage. Now the retry stage would trigger further actions like sending follow up emails etc. Likewise, dispatch stage would have a different set of actions. Since every order is important and we need to know where it stands, using Camunda Platform is imperative. Camunda Platform might not be a right choice where just a one off thing needs to be done. For example, uploading of product information by user or periodic processing of heavy images by a worker. These are all either one step processes or periodic automated processes where we can track the status without using a business modeler like Camunda Platform.

Incentivized

• In charge of the ETL processes.
• As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.

Incentivized

• Asynchronous functionality of Camunda Platform and different types of gateways.

• they should bring in some time based scheduling too not only event based
• they do not store the metadata due to which we are not able to analyze the workflows
• they only support python as of now for scripted pipeline writing

Incentivized

• Camunda expects that you will develop your own user interfaces. This is either a benefit or a barrier depending on your perspective on packaged UI.
• As an open source vendor, Camunda is under-covered in analyst reports.

Easy to learn Easy to use Robust workflow orchestration framework Good in dependent job management

Incentivized

Camunda provides pretty standard product support offerings.

There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.

Incentivized

Lacks good documentation. Training and documentation is geared towards those who are already technically adept. Does not have as many data integrations as other full fledged products. Paid version of Camunda is not as fully fledged as other products.

Incentivized

• A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
• Allowed us to implement complex data pipelines easily and at a relatively low cost

Incentivized

• The positive impact is that we are able to ensure the business process is being followed and that results in orders getting processed successfully leading to customer satisfaction and revenue
• Another positive impact is that we are able to track any anomalies and any errors in the order flow and retry them so that users don't have a negative experience.
• A negative point is that it is an overhead to maintain so there is significant engineering effort getting invested there

Incentivized