We performed a comparison between Azure Data Factory and Microsoft Parallel Data Warehouse 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."We haven't had any issues connecting it to other products."
"The user interface is very good. It makes me feel very comfortable when I am using the tool."
"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."
"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"Powerful but easy-to-use and intuitive."
"The function of the solution is great."
"The overall performance is quite good."
"Data Factory's most valuable feature is Copy Activity."
"We have complete control over our data."
"One of the most important features is the ease of using MS SQL."
"Tools like the BI and SAS are excellent."
"I am very satisfied with the customer service/technical support."
"It is not a pricey product compared to other data warehouse solutions."
"I like Data Warehouse's data integrity features. Data integrity is what databases are made for as opposed to spreadsheets."
"The most valuable features are the performance and usability."
"The most valuable feature of this solution is performance."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"The Microsoft documentation is too complicated."
"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."
"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."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"They need to incorporate a machine learning engine."
"The only issue with the product is that the process is very slow when we have a huge amount of data."
"SQL installation is pretty tricky. The scalability and customer support also should be improved."
"Some compatibility issues occur during deployment, so we need to build the product from scratch for some features."
"The query is slow if we don't optimize it."
"Concurrent queries are limited to 32, making it more of a data storage mechanism instead of an active DWH solution."
"I would like the tool to support different operating systems."
"I would like to see better visualization features."
More Microsoft Parallel Data Warehouse Pricing and Cost Advice →
Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while Microsoft Parallel Data Warehouse is ranked 8th in Data Warehouse with 32 reviews. Azure Data Factory is rated 8.0, while Microsoft Parallel Data Warehouse is rated 7.6. 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 Microsoft Parallel Data Warehouse writes "An easy to setup tool that allows its users to write stored procedure, making it a scalable product". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas Microsoft Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, SAP BW4HANA, Snowflake and VMware Tanzu Greenplum. See our Azure Data Factory vs. Microsoft Parallel Data Warehouse report.
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