Compare - Google Cloud Dataflow VS Streamlit
Here’s the difference between Google Cloud Dataflow and Streamlit. The comparison is based on pricing, deployment, business model, and other important factors.
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.
About Streamlit
The fastest way to build and deploy data apps. Streamlit is the first app framework built specifically for Machine Learning and Data Science teams.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Data Apps |
| Stage | Late Stage | Early Stage |
| Target Segment | Enterprise, Mid size | Mid size, Enterprise |
| Deployment | SaaS | Open Source |
| Business Model | Commercial | Commercial |
| Pricing | Freemium | Free Trial |
| Location | US | San Francisco, California, United States |
| Companies using it | ||
| Contact info |
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