Compare - Google Cloud Dataflow VS Onehouse
Here’s the difference between Google Cloud Dataflow and Onehouse. 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 Onehouse
Onehouse delivers a new bedrock for your data, through a cloud-native managed lakehouse service built on Apache Hudi, which was created by the founding team while they were at Uber. Onehouse makes it possible to blend the ease of use of a warehouse with the scale of a data lake, by offering a seamless experience for engineers to get their data lakes up and running.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Data Lakes |
| Stage | Late Stage | Early Stage |
| Target Segment | Enterprise, Mid size | SMBs, Mid-size, Enterprise |
| Deployment | SaaS | Open source |
| Business Model | Commercial | Commercial |
| Pricing | Freemium | Conatct Sales |
| Location | US | Menlo Park, California |
| Companies using it | ||
| Contact info |
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