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."Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"An excellent tool for pipeline orchestration."
"The security of the agent that is installed on-premises is very good."
"I am one hundred percent happy with the stability."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"The most valuable feature of this solution would be ease of use."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"The computational power of Snowflake is very good."
"One of the valuable features is the solution’s time travel capability. The solution is highly stable. The solution is highly scalable. The initial setup is straightforward, and the deployment process is quick and efficient. I recommend the solution. Overall, I rate it a perfect ten."
"It is quite a convenient tool."
"Its performance speed is very good."
"Snowflake Analytics' most valuable feature is its inbuilt infrastructure for executing queries, which I don't have to manage based on my data volume as it's taken care of by Snowflake."
"What we found most valuable in Snowflake Analytics are its attributes that are very convenient for business use such as data sharing, cloning, time travel, and fail-safe. It's a good product all in all."
"The advanced features like time travel, zero copy cloning and scalability have been most useful. Snowflake requires zero maintenance for Data Warehousing on the cloud system."
"It ensures the optimization of the application development while maintaining the user-friendly nature of its UI."
"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
"The one element of the solution that we have used and could be improved is the user interface."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"Some known bugs and issues with Azure Data Factory could be rectified."
"There is no built-in pipeline exit activity when encountering an error."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"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."
"Snowflake Analytics can improve the integration with machine learning tools and AI and it will make the solution more usable."
"Snowflake's Snowpark is an area of concern where improvements are required."
"There are issues while loading data from Snowflake Analytics to the Power BI reporting."
"The product's cost is an area of concern where improvements are required."
"Snowflake could improve in the areas of advanced machine learning AML and generative AI."
"Implementing everything on-premise is challenging because it require proper support from advisors, DBAs, and others."
"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."
"The scheduling of jobs requires improvement, particularly in terms of the user interface which currently lacks certain features found in comparable platforms."
Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while Snowflake Analytics is ranked 6th in Cloud Data Warehouse with 30 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 Microsoft Azure Synapse Analytics, 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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