Compare - Google Cloud Dataflow VS Pace
Here’s the difference between Google Cloud Dataflow and Pace. 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 Pace
Pace integrates natively with your business's most important data sources, unify and transform this disparate data into a standardized format that makes intuitive sense for B2B sellers, and that can be easily synced and used by CRMs. With Pace, you can see which insights drive positive sales behaviors and, by extension, the outcomes you care about. So, you can build a set of repeatable sales motions
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | PLG CRM |
| Stage | Late Stage | Early Stage |
| Target Segment | Enterprise, Mid size | SMB's, Mid- size |
| Deployment | SaaS | SaaS |
| Business Model | Commercial | Commercial |
| Pricing | Freemium | Contact Sales |
| Location | US | New York, NY |
| Companies using it | ||
| Contact info |
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