We performed a comparison between Azure Data Factory and IBM Infosphere DataStage based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Azure Data Factory 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 better understand the data flow. Users are happier with its pricing as well. Once IBM Infosphere DataStage moves toward a focus on cloud technologies, it will become a more desirable solution in today’s cloud-focused marketplace.
"Allows more data between on-premises and cloud solutions"
"I can do everything I want with SSIS and Azure Data Factory."
"Its integrability with the rest of the activities on Azure is most valuable."
"The flexibility that Azure Data Factory offers is great."
"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."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"The scalability of the product is impressive."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"The product is easy to deploy."
"ETL is the most valuable feature."
"The most valuable feature is the ability to transfer information via notes."
"Once you have Infosphere up and running properly, it is stable."
"Compared to other ETL tools, DataStage has excellent debugging and development capabilities. And the availability of connectors, even though we sometimes have to opt for specific ones. Also, the availability of patches is good."
"We like the flexibility of modeling."
"We can view what we want to do. We can transform data and put them on tables."
"I am impressed with the tool's ETL tracing."
"Some known bugs and issues with Azure Data Factory could be rectified."
"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."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"We have experienced some issues with the integration. This is an area that needs improvement."
"The setup is extremely difficult."
"Its documentation is not up to the mark. While building APIs, we had a lot of problems trying to get around it because it is not very user-friendly. We tried to get hold of API documentation, but the documentation is not very well thought out. It should be more structured and elaborate. In terms of additional features, I would like to see good reporting on performance and performance-tuning recommendations that can be based on AI. I would also like to see better data profiling information being reported on InfoSphere."
"The error messaging needs to be improved."
"The solution can be a bit more user-friendly, similar to Informatica."
"It would be great if they can include some basic version of data quality checking features."
"The interface needs improvement. It is really too technical. That is the main problem."
"The troubleshooting guide is very bad."
"DataStage is quite expensive. It is too hard to find a consultant using DataStage in Turkey."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while IBM InfoSphere DataStage is ranked 7th in Data Integration with 37 reviews. Azure Data Factory is rated 8.0, while IBM InfoSphere DataStage is rated 7.8. 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 IBM InfoSphere DataStage writes "User-friendly with a lot of functions for transmission rules, but has slow performance and not suitable for a huge volume of data". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas IBM InfoSphere DataStage is most compared with IBM Cloud Pak for Data, SSIS, Talend Open Studio, Informatica PowerCenter and IBM InfoSphere Information Server. See our Azure Data Factory vs. IBM InfoSphere DataStage 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.