Compare - Argo VS Google Cloud Dataflow
Here’s the difference between Argo and Google Cloud Dataflow. The comparison is based on pricing, deployment, business model, and other important factors.
About Argo
Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition).
About Google Cloud Dataflow
Google Cloud Dataflow is a cloud-based data processing service for both batch and real-time data streaming applications. It enables developers to set up processing pipelines for integrating, preparing and analyzing large data sets, such as those found in Web analytics or big data analytics applications. The Cloud Dataflow software expands on earlier Google parallel processing projects, including MapReduce, which originated at the company. Cloud Dataflow is designed to bring to entire analytics pipelines the style of fast parallel execution that MapReduce brought to a single type of computational sort for batch processing jobs.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Workflow Orchestration | Data Streaming |
| Stage | Mid Stage | Late Stage |
| Target Segment | Enterprise, Mid size | Enterprise, Mid size |
| Deployment | On Prem | SaaS |
| Business Model | Open Source | Commercial |
| Pricing | Freemium | Freemium |
| Location | US | US |
| Companies using it | ||
| Contact info |
Add to compare
