We performed a comparison between Aster Data Map Reduce and Azure Data Factory 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 most valuable feature is the ease of uploading data from multiple sources."
"It's stable and reliable."
"The ease of deployment is useful so clients are up and running quickly in comparison to other products."
"The most valuable feature is the copy activity."
"We have been using drivers to connect to various data sets and consume data."
"We use the solution to move data from on-premises to the cloud."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"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."
"Allows more data between on-premises and cloud solutions"
"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"There are some ways that the handling of unstructured data could be improved."
"It is hard for some of our users to set up rules for cleansing and transforming data, so this is something that could be improved."
"From my perspective, it would be good if they gave better ITIN/R plugins to use the data for AI modeling, or data science modeling. We can do it now; however, it could be more elegant in terms of interfacing."
"I have not found any real shortcomings within the product."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"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."
"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."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
Aster Data Map Reduce is ranked 20th in Data Warehouse with 3 reviews while Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews. Aster Data Map Reduce is rated 7.4, while Azure Data Factory is rated 8.0. The top reviewer of Aster Data Map Reduce writes "Has good base product functionality of data storage and analytics but there should be an option to use it on the cloud ". On the other hand, the top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". Aster Data Map Reduce is most compared with , whereas Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage. See our Aster Data Map Reduce vs. Azure Data Factory report.
See our list of best Cloud Data Warehouse vendors.
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
