We performed a comparison between Azure Data Factory and SAS Data Management based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"Powerful but easy-to-use and intuitive."
"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
"An excellent tool for pipeline orchestration."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"The tool is reliable, quick, and powerful."
"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."
"I am impressed with the tool's ability to customize."
"This is an established product with powerful data analysis and varied options for user entry points."
"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."
"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."
"The product offers very good flexibility."
"The technical support is excellent."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"We require Azure Data Factory to be able to connect to Google Analytics."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"Azure Data Factory's pricing in terms of utilization could be improved."
"The support and the documentation can be improved."
"When working with AWS, we have noticed that the difference between ADF and AWS is that AWS is more customer-focused. They're more responsive compared to any other company. ADF is not as good as AWS, but it should be. If AWS is ten out of ten, ADF is around eight out of ten. I think AWS is easier to understand from the GUI perspective compared to ADF."
"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."
"We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows."
"I would like the tool to include the ability to automate the modifications of the integrations."
"The pricing of the solution needs to be improved. They need to work to make it more affordable."
"With SAS Data Management, you have to purchase an external driver, configure all of the tables for all of the data that you will extract from Salesforce. It's not a straightforward process."
"The solution is quite expensive and hard to install/configure."
"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."
"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while SAS Data Management is ranked 43rd in Data Integration with 15 reviews. Azure Data Factory is rated 8.0, while SAS Data Management is rated 8.4. 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 SAS Data Management writes "A scalable solution with customer support that is responsive and diligent". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas SAS Data Management is most compared with Informatica PowerCenter, Tungsten RPA, Microsoft Purview Data Governance, SSIS and IBM InfoSphere DataStage. See our Azure Data Factory vs. SAS Data Management report.
See our list of best Data Integration vendors.
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.
