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.
"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."
"The initial setup is very quick and easy."
"The data copy template is a valuable feature."
"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."
"The solution can scale very easily."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"The most valuable feature is the logging capability."
"The feature of SAP Data Services has enhanced our company's business processes because we are able to run around 800 jobs in areas like data extraction and transaction objects."
"The most valuable features of SAP Data Services lie in its ability to effectively observe and interpret the information within data related to people or facts, stands out."
"The basic functionality is quite good as is the basic logic and data information."
"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 initial setup is not complex."
"I appreciate having access to the SAP data."
"I have worked with Data Services for a long time, and currently, I find the dashboarding and reporting part to be the most valuable function."
"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"It would be better if it had machine learning capabilities."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"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."
"I have not found any real shortcomings within the product."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"The description of error messages isn't extensive, although they point to the problem. With other solutions, like Talend, I was able to use the debugger to get directly to the problem, but with SAP Data Services the debugger is not working. I'm not sure if it's a problem with the version specifically, but I'm using it in an enterprise environment and I can't do an upgrade."
"The solution should offer more machine learning and automation."
"The execution engines and processing engines have shortcomings and need improvements."
"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."
"With SAP Data Services, the problem arises when I try to connect to Azure Databricks."
"Data Services SAP is lacking in sources and target databases compared to Informatica. SAP Data Services should have more connectivity."
"The initial setup is complex."
"It's an ETL that is very good with relational databases but not as good with files and semi-structured files."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while SAP Data Services is ranked 10th in Data Integration with 45 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 data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of SAP Data Services writes "Responsive support, scalable, and beneficial integration". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and AWS Lake Formation, whereas SAP Data Services is most compared with Syniti Data Quality, Informatica PowerCenter, SAP Process Orchestration, Palantir Foundry and SSIS. 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.