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."On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."
"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"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."
"The most valuable aspect is the copy capability."
"The most valuable feature is the copy activity."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"We like that this solution includes a developer edition, free of charge, to allow for training."
"I have found its most valuable features to be its package management capabilities and the flexibility it offers in designing workflows."
"The data reader is the most valuable feature."
"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."
"The UI is very user-friendly."
"It is easy to set up the product."
"It's saved time using visualization descriptions."
"The interface is very user-friendly."
"It can improve from the perspective of active logging. It can provide active logging information."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."
"Data Factory's performance during heavy data processing isn't great."
"Some known bugs and issues with Azure Data Factory could be rectified."
"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."
"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."
"There was also not enough instructions from Microsoft in regards to this application or this technology, which can easily be improved upon."
"SSIS can improve by the minimum code requirements in stored procedures and exporting data is difficult. They could make it easier, it should be as easy as it is to import data."
"I come from a coding background and this tool is graphically based. Sometimes I think it's cumbersome to do mapping graphically. If there was a way to provide a simple script, it would be helpful and make it easier to use."
"SSIS is stable, but extensive ETL data processing can have some performance issues."
"I would like to see more standard components out of the box, such as SFTP, and Data Compression components."
"The creation of the measure in the DAC's model could be improved."
"Performance could be better."
"Sometimes we need to connect to AWS to get additional data sources, so we have to install some external LAN and not a regular RDBMS. We need external tools to connect. It would be great if SSIS included these tools. I'd also like some additional features for row indexing and data conversion."
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 Qlik Replicate, 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.
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.
