We performed a comparison between Azure Data Factory and SAP Data Services based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Users prefer Azure Data Factory, as it is mature, robust, and consistent. The built-in connectors of more than 100 sources and onboarding data from many different sources to the cloud environment make it easier for users to understand the data flow better. An experienced data engineer is recommended to ensure proper speed and functionality when using SAP Data Services; it is not recommended for the novice user.
"We have been using drivers to connect to various data sets and consume data."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"Powerful but easy-to-use and intuitive."
"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."
"It is easy to integrate."
"We use the solution to move data from on-premises to the cloud."
"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."
"We have found the bulk load feature very valuable."
"The product's most valuable features are data validation and rules."
"We can extract data at a table level, extract data at the ETL level, and we can extract data at an ODP level."
"The reporting on the data, even from third-party software, is very good."
"You can always manipulate a lot of things as long as you have the skill level."
"The fact that it's built on SQL, it makes it easy to write code. The database and the connection are quite smooth."
"The HANA database, which is very fast, is a valuable feature."
"Its integration capabilities and the data migration capabilities are the most valuable. It is very good for SAP and non-SAP tools. It has very good integration with SAP, but it also has the capabilities to connect to other systems. We find it very helpful and stable."
"The maintenance of data services is the solution's most valuable feature."
"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 are limitations when processing more than one GD file."
"The Microsoft documentation is too complicated."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"When the record fails, it's tough to identify and log."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"They could make it easier to work with web services."
"With SAP Data Services, the problem arises when I try to connect to Azure Databricks."
"Integration with other products could be improved."
"We encounter challenges while exporting implemented rules, such as those applied to objects like the material master, into a format like Excel for documentation and further analysis."
"I want some more business intelligence applications. People need to know more and more about data, including the transformation rules, etc. Informatica is a better product for data cataloging. SAP should update the data catalog."
"In the future, Data Services should offer a cloud version."
"It's an ETL that is very good with relational databases but not as good with files and semi-structured files."
"It will work fine only in an SAP environment. It could be said that the integration with other vendors could be better."
Azure Data Factory is ranked 1st in Data Integration with 40 reviews while SAP Data Services is ranked 10th in Data Integration with 15 reviews. Azure Data Factory is rated 8.0, while SAP Data Services is rated 8.0. The top reviewer of Azure Data Factory writes "The good, the bad and the lots of ugly". On the other hand, the top reviewer of SAP Data Services writes "Easy to use, simple to implement, and offers very good mapping capabilities". Azure Data Factory is most compared with Informatica PowerCenter, Alteryx Designer, Informatica Cloud Data Integration, Snowflake and AWS Lake Formation, whereas SAP Data Services is most compared with Syniti Data Quality, Informatica PowerCenter, SSIS, Palantir Foundry and SAP Process Orchestration. See our Azure Data Factory vs. SAP Data Services report.
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We monitor all Data Integration 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.