Compare - Google Cloud Dataflow VS Cube
Here’s the difference between Google Cloud Dataflow and Cube. 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 Cube
Cube is the headless business intelligence platform for accessing data from modern data stores, organizing it into consistent definitions, and delivering it to every application. Cube works with all kinds of data sources and delivers data to any BI tool or data app.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Metrics Store |
| Stage | Late Stage | Mid Stage |
| Target Segment | Enterprise, Mid size | Mid size, Enterprise |
| Deployment | SaaS | Open sourceSaaS |
| Business Model | Commercial | Open Source, Commercial |
| Pricing | Freemium | Freemium |
| Location | US | San Francisco |
| Companies using it | ||
| Contact info |
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