Here’s the difference between Cazena and Google Cloud Dataflow. The comparison is based on pricing, deployment, business model, and other important factors.
Cazena provides managed cloud service for end-to-end big data service. It acts as an extension to the enterprise infrastructure and enables to run workloads in the cloud. It has intelligence built in to deploy infrastructure for Hadoop, MPP SQL, Spark or search based on the workload. Existing BI tools could be used to analyze the data as if it were present in local. Its use cases include overloaded datacenter, simplifying analytic pipelines, as a sandbox environment, as a data lake etc.
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.
Overview | ||
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Categories | Data Lakes | Data Streaming |
Stage | Mid Stage | Late Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaS | SaaS |
Business Model | Commercial | Commercial |
Pricing | Contact Sales | Freemium |
Location | US | US |
Companies using it | ||
Contact info |