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 initial setup is very quick and easy."
"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."
"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."
"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."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"Time Travel and Snowpipe are good features."
"It ensures the optimization of the application development while maintaining the user-friendly nature of its UI."
"Scaling is very high – there's no problem for scaling purposes. The learning curve is very small. And there are a lot of advanced features like handling duplicates, security, data governance, data sharing, and data cloning."
"It is quite a convenient tool."
"It helps with business intelligence by providing analytics that can be reported."
"The solution auto-scales and it provides concurrency."
"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."
"Very good flexibility and it offers computation completely decoupled from the storage."
"The pricing model should be more transparent and available online."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"Data Factory's performance during heavy data processing isn't great."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"When the record fails, it's tough to identify and log."
"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."
"I cannot comment on the product's stability because we are still struggling with its performance."
"The technical support is not very good."
"The platform could work easier for AI implementation compared to one of its competitors."
"The solution’s scalability could be improved."
"The UI could be more user-friendly."
"Machine learning in Snowflake isn't as advanced as in other products. I haven't heard of any successful industry-wide use cases of machine learning implemented in Snowflake. It might take a couple of years to reach the same level as Databricks."
"Machine learning should be improved."
"The solution's high price can be an area of concern that needs improvement."
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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