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."I like that it's a monolithic data platform. This is why we propose these solutions."
"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."
"We have found the bulk load feature very valuable."
"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 most valuable feature is the copy activity."
"Data Factory's best features are simplicity and flexibility."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"The scalability of SSIS is good."
"We can connect with multiple data sources easily using an external connector in SSIS."
"The most valuable feature of SSIS is that it can handle real complex transformations."
"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 most valuable feature of SSIS is that you can take data from other servers which are not MS SQL Server or Oracle."
"I have used most of the standard SQL features, but the ones that stand out are the Data Flows and Bulk Import."
"The solution is easy to use and developer friendly."
"The performance is good."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"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 are limitations when processing more than one GD file."
"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."
"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."
"The deployment should be easier."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"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."
"Improvement as per customer requirements."
"A change in the metadata source cripples the whole ETL process, requiring each module to be manually reopened."
"I would like to see more features in terms of the integration with Azure Data Factory."
"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."
"We'd like them to develop data exploration more."
"You have to write push down join & lookup SQL to the database yourself via stored procedures or use of the SQL Task to get very high performance. That said, this is a common complaint for nearly all ETL tools on the market and those that offer an alternative such as Informatica offer them at a very expensive add-on price."
"There are a lot of things that Microsoft could improve in relation to SSIS. One major problem we faced was when attempting to move some Excel files to our SQL Server. The Excel provider has a limitation that prevents importing more than 255 columns from a particular Excel file to the database. This restriction posed a significant issue for us."
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 Talend Open Studio, 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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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.
