We performed a comparison between Azure Data Factory and SSIS 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."For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The initial setup is very quick and easy."
"The most important feature is that it can help you do the multi-threading concepts."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"The solution has a good interface and the integration with GitHub is very useful."
"The most valuable features are data transformations."
"It is easy to deploy workflows and schedule jobs."
"It's a competent product."
"The most valuable feature of SSIS is its ease of use. It is easier to use than other applications."
"The script component is very powerful, things that you cannot normally do, is feasible through C#."
"It is also easy to learn and user-friendly. Microsoft is also good in terms of technical support. They have built a large community all over the world."
"The reporting on the solution is perfect. I didn't expect to see reporting features, but they are great."
"The UI is very user-friendly."
"The most valuables features are the relatively short learning curve, and the automation capabilities provided through the BIML add-in for SSDT."
"It has a drag and drop feature that makes it easy to use. It has a good user experience because it takes into account your most-used tools and they're lined up nicely so you can just drag and drop without looking too far. It also integrates nicely with Microsoft."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"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."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"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."
"Data Factory's cost is too high."
"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."
"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"We're in the process of switching to Informatica, and we need to work out data lineage and data profiling and to improve the quality of our data. SSIS, however, is not that compatible with Informatica. We managed to connect it to Informatica Metadata Manager, but we don't get good lineage, so we have to redo all our ETLs using the Informatica process in order to accept the proper data lineage."
"In terms of its performance, it could be better. That could be something that would be easy and welcomed as an upgrade."
"I would like to see more standard components out of the box, such as SFTP, and Data Compression components."
"Sometimes when we want to publish to other types of databases it's not easy to publish to those databases. For example, the Jet Database Engine. Before the SSIS supported Jet Database Engine but nowadays it doesn't support the Jet Database Engine. We connect to many databases such as Access database, SparkPros databases and the other types of databases using Jet Database Engines now and SSIS now doesn't seem to support it in our databases."
"A change in the metadata source cripples the whole ETL process, requiring each module to be manually reopened."
"The performance of SSIS could improve when comparing it to Oracle Database."
"I have a tool called ZappySys. I need that tool to cut down on the complexity of SSIS. That tool really helps with a quick turnaround. I can do things quickly, and I can do things accurately. I can get better reporting on errors."
"I would also like to see full integration with our BI because then our full load of data will be available in our organization. They should incorporate an ATL process."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while SSIS is ranked 2nd in Data Integration with 69 reviews. Azure Data Factory is rated 8.0, while SSIS is rated 7.6. 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 SSIS writes "Maintaining the solution and contacting its support team is easy". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Matillion ETL, whereas SSIS is most compared with Informatica PowerCenter, Talend Open Studio, IBM InfoSphere DataStage, Oracle Data Integrator (ODI) and Alteryx Designer. See our Azure Data Factory vs. SSIS report.
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