We performed a comparison between Aster Data Map Reduce and Azure Data Factory based on real PeerSpot user reviews.
Find out what your peers are saying about Snowflake Computing, Microsoft, Amazon Web Services (AWS) and others in Cloud Data Warehouse."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."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"It is easy to deploy workflows and schedule jobs."
"From what we have seen so far, the solution seems very stable."
"Data Factory's best features are simplicity and flexibility."
"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."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"Its integrability with the rest of the activities on Azure is most valuable."
"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."
"There are some ways that the handling of unstructured data could be improved."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"The pricing model should be more transparent and available online."
"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."
"Data Factory's performance during heavy data processing isn't great."
"The Microsoft documentation is too complicated."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"There is no built-in pipeline exit activity when encountering an error."
Aster Data Map Reduce is ranked 19th 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 Microsoft Azure Synapse Analytics.
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