Camunda vs. Google Cloud Dataflow

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

Based on my experience, streaming / real time / machine learning / AI type of processing and batch processing which needs less transformation are very well suited. Work load that needs complex transformation / multiple hops gets very complicated to implement. New feature like Dataflow SQL option will come in handy for sql heavy users.

• Task orchestration
• Freeware
• Graphical interface allows normal users to understand business process model diagrams more intuitively

Incentivized

• Streaming, Real time work load
• Batch processing
• Auto scaling
• flexible pricing

• Documentation - It is usually daunting for beginners because of lack of good documentation
• Simplified setup on local machine for Camunda Server would help developers test changes quickly
• Easier migration from one deployment version of a Camunda process to another deployment version would help in making changes and deploying them faster.
• Heap memory management becomes issue at times resulting in stuck processes. This needs to be resolved.

Incentivized

• inbuild template options can be expanded
• more data connector options
• easy of use

Camunda provides pretty standard product support offerings.

Google Cloud Dataproc Cloud Datafusion

• We've built a good business around developing and deploying Camunda for our clients over the last 7 years.
• Our clients are finding it a cost-effective way to try before they buy.
• There's an over-reliance on big offshore outsourcing shops, which hurts ROI and success rates.

• cost saving from managing our own data center for ETL servers
• consumption based pricing
• with auto scaling feature, we were able to expand components to support work load