We performed a comparison between Azure Data Factory and Snowflake Analytics based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"Its integrability with the rest of the activities on Azure is most valuable."
"Considering everything I have accessed, the product's dashboard is good since it provides multiple good options, including customization options."
"Features like the fact that the solution is very fast and available on the cloud are some of the valuable attributes of the solution."
"Snowflake Analytics is pretty easy to use with the connectors for integration with the tools and systems in my company."
"It ensures the optimization of the application development while maintaining the user-friendly nature of its UI."
"Deployment is straightforward as it's a SaaS product. No maintenance required."
"It's a scalable solution because you can analyze a huge amount of data in the solution."
"One of the key advancements in Snowflake Analytics is data sharing."
"Time Travel and Snowpipe are good features."
"The number of standard adaptors could be extended further."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"Data Factory's performance during heavy data processing isn't great."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"The one element of the solution that we have used and could be improved is the user interface."
"The product's cost is an area of concern where improvements are required."
"The distribution methodology isn't as strong as Bethesda or SAP HANA. It's not as strong as other competitors."
"The solution needs to consider including some updates in the future."
"The solution’s scalability could be improved."
"Integration into different Python and Jupyter notebooks needs to be improved."
"The platform's data governance space needs more capability."
"Snowflake should include a WHERE clause for building data pipelines."
"The tool should support EIM use cases. I guess the product is already working on it. I look forward to seeing inbuilt AI generative tools in the solution's future releases. The tool's price can be a little lower. The solution's on-premises support is also very limited. We have to rely on other support services to deploy it on-premises."
Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while Snowflake Analytics is ranked 6th in Cloud Data Warehouse with 31 reviews. Azure Data Factory is rated 8.0, while Snowflake Analytics is rated 8.4. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of Snowflake Analytics writes "A scalable tool useful for data lake and data mining processes". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas Snowflake Analytics is most compared with Adobe Analytics, Mixpanel, Amplitude, Glassbox and Yellowbrick Cloud Data Warehouse. See our Azure Data Factory vs. Snowflake Analytics report.
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