Compare - Google Cloud Dataflow VS Databand
Here’s the difference between Google Cloud Dataflow and Databand. 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 Databand
Databand is a provider of cloud and AI based data observability solutions. It provides an AI platform for unified data pipeline monitoring. It allows data scientists, data engineers, and data analysts to build, manage and optimize their processes for model training, experimentation, testing, and deployment. It is saturated with DataOps in providing automation and integration solutions through a pipeline framework for machine learning and iterative data products.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Data Quality Monitoring |
| Stage | Late Stage | Early Stage |
| Target Segment | Enterprise, Mid size | Mid size, Enterprise |
| Deployment | SaaS | SaaS |
| Business Model | Commercial | Commercial |
| Pricing | Freemium | Contact Sales |
| Location | US | New York, US |
| Companies using it | ||
| Contact info |
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