Compare - Starburst VS Google Cloud Dataflow
Here’s the difference between Starburst and Google Cloud Dataflow. The comparison is based on pricing, deployment, business model, and other important factors.
About Starburst
For data-driven companies, Starburst offers a full-featured data lake analytics platform, built on open source Trino. Our platform includes the capabilities needed to discover, organize, and consume data without the need for time-consuming and costly migrations. We believe the lake should be the center of gravity, but support accessing data outside the lake when needed. With Starburst, teams can access more complete data, lower the cost of infrastructure, use the tools best suited to their specific needs, and avoid vendor lock-in. Trusted by companies like Comcast, Grubhub, and Priceline, Starburst helps companies make better decisions faster on all their data.
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 | Data Lakes, Data Mesh | Data Streaming |
| Stage | Mid Stage | Late Stage |
| Target Segment | Enterprise, Mid size | Enterprise, Mid size |
| Deployment | SaaSOn Prem | SaaS |
| Business Model | Commercial | Commercial |
| Pricing | Contact Sales | Freemium |
| Location | US | US |
| Companies using it | ||
| Contact info |
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