Compare - Google Cloud Dataflow VS Nexla
Here’s the difference between Google Cloud Dataflow and Nexla. 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 Nexla
Nexla is the leader in unified data operations and a 2021 Gartner Cool Vendor. This platform makes it simple for anyone to create scalable data flows. Teams working with data get a no/low-code unified experience to integrate, transform, provision, and monitor data for any use case. Data users with varying skill levels work collaboratively to create ready-to-use data products. As a result, organizations get zero-friction, governed, and agile data operations.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Data Mesh, Reverse ETL Tools |
| Stage | Late Stage | Mid Stage |
| Target Segment | Enterprise, Mid size | Enterprise, Mid size |
| Deployment | SaaS | SaaS |
| Business Model | Commercial | Commercial |
| Pricing | Freemium | Contact Sales |
| Location | US | San Mateo, California |
| Companies using it | ||
| Contact info |
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