Users are reliant on Azure itself for new features. This should be taken into consideration: even though nightly copies of your on-premise database to the cloud might be plain sailing for ADF, you should also make sure that your on-premise systems can handle the load.īuilding custom activities and integrations is not included within the service. Note that extracting data from on -premise data sources will however incur a load on these systems. As a result, the user should not be concerned about the resource usage of the ETL pipelines. The underlying resources and infrastructure are fully managed by Azure.
#Prefect vs airflow software
This software is installed on a machine that can access the on-premise data source and can be considered as a secure “tunnel” to Azure. One of the most appealing features of ADF is the seamless integration with on-premise data sources through the Integration Runtime (IR). This means there is no fixed cost and pricing is fully dependent on the number of pipeline-runs and their resource utilization.
This also applies to creating your first pipelines.ĪDF is a “pay-as-you-go” solution. Getting started with ADF is effortless accessing the services is only a matter of a few clicks. Although ADF includes the possibility of including custom code, the majority of the work is conducted using the graphical user interface. In this article, we provide an insight on the pros and cons of both tools, as well as the potential of using them in a combined setup.Īzure Data Factory What is Azure Data Factory?Īzure Data factory (hereafter “ADF”) is a service offered by Microsoft within Azure for constructing ETL and ELT pipelines. At element61, we’re fond of Azure Data Factory and Airflow for this purpose.
Although the development phase is often the most time-consuming part of a project, automating jobs and monitoring them is essential to generate value over time. As data professionals, our role is to extract insight, build AI models and present our findings to users through dashboards, API’s and reports.
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