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 data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"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 trigger scheduling options are decently robust."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"The scalability of the product is impressive."
"The platform not only provides ease of use but also stands out for its speedy execution, conveying a sense of robustness and reliability that I find appealing."
"Time Travel and Snowpipe are good features."
"I am impressed with the product's data-sharing feature."
"Features like the fact that the solution is very fast and available on the cloud are some of the valuable attributes of the solution."
"It can run complex workloads with varied compute."
"It is quite a convenient tool."
"The most valuable features of Snowflake for our data analytics are its time travel capability, allowing easy data recovery, and its automatic optimization of partitioning and clustering."
"It is an all-in-one platform that provides the capabilities needed for various analytics tasks, including data warehousing for machine learning."
"The solution needs to be more connectable to its own services."
"Some of the optimization techniques are not scalable."
"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."
"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."
"I have not found any real shortcomings within the product."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."
"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 solution’s interface is good but it could be improved."
"One area that could benefit from enhancement is the user interface for more visual ESM features."
"The solution’s scalability could be improved."
"Implementing everything on-premise is challenging because it require proper support from advisors, DBAs, and others."
"The distribution methodology isn't as strong as Bethesda or SAP HANA. It's not as strong as other competitors."
"Snowflake's Snowpark is an area of concern where improvements are required."
"The UI must be improved."
"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 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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