Compare - Google Cloud Dataflow VS AWS Kinesis
Here’s the difference between Google Cloud Dataflow and AWS Kinesis. 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 AWS Kinesis
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.
Comparison Table
| Overview | ||
|---|---|---|
| Categories | Data Streaming | Data Streaming |
| Stage | Late Stage | Late Stage |
| Target Segment | Enterprise, Mid size | Enterprise, Mid size |
| Deployment | SaaS | SaaS |
| Business Model | Commercial | Commercial |
| Pricing | Freemium | Contact Sales |
| Location | US | US |
| Companies using it | ||
| Contact info |
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