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AWS Step Functions vs Google Cloud Dataflow: What are the differences?
AWS Step Functions: Build Distributed Applications Using Visual Workflows. AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly; Google Cloud Dataflow: A fully-managed cloud service and programming model for batch and streaming big data processing. Google Cloud Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.
AWS Step Functions belongs to "Cloud Task Management" category of the tech stack, while Google Cloud Dataflow can be primarily classified under "Real-time Data Processing".
According to the StackShare community, Google Cloud Dataflow has a broader approval, being mentioned in 32 company stacks & 8 developers stacks; compared to AWS Step Functions, which is listed in 19 company stacks and 7 developer stacks.
Pros of AWS Step Functions
- Integration with other services6
- Easily Accessible via AWS Console4
- Complex workflows4
- High Availability2
- Workflow Processing2
Pros of Google Cloud Dataflow
- Unified batch and stream processing5
- Fully managed3
- Throughput Transparency1