Compare - Google Cloud Dataflow VS Apache Hudi
Here’s the difference between Google Cloud Dataflow and Apache Hudi. 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 Apache Hudi
Hudi is a rich platform to build streaming data lakes with incremental data pipelines on a self-managing database layer, while being optimized for lake engines and regular batch processing.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Data Lakes |
| Stage | Late Stage | Early Stage |
| Target Segment | Enterprise, Mid size | Mid Size, Enterprise |
| Deployment | SaaS | Open Source |
| Business Model | Commercial | Open Source |
| Pricing | Freemium | Freemium |
| Location | US | California, US |
| Companies using it | ||
| Contact info |
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