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Azure Data Factory vs IBM InfoSphere Information Server comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
IBM InfoSphere Information ...
Ranking in Data Integration
30th
Average Rating
8.2
Reviews Sentiment
5.8
Number of Reviews
9
Ranking in other categories
Metadata Management (6th)
 

Mindshare comparison

As of February 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.0%, down from 9.8% compared to the previous year. The mindshare of IBM InfoSphere Information Server is 1.0%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.0%
IBM InfoSphere Information Server1.0%
Other96.0%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
MI
Senior Data Engineer at Mohammed Mansour Alrumiah
Faced challenges with customer support and documentation but have benefited from reliable data integration over the years
As for utilizing the platform's metadata management feature, I have not worked on that feature yet, but personally, I have done that. To evaluate the effectiveness of IBM InfoSphere Information Server's data integration capabilities, if IBM is providing all the solutions we are using, then it is definitely a helpful thing. Mostly, the other thing is that it is a big area including data governance, data lineage, data management, and metadata, but every customer is not putting that much effort and money on that. They mostly migrate the data, use it, and forget it, but slowly things are changing. I am working in Saudi Arabia, so here also data governance, data management, and those kinds of things are getting attention. Regarding how scalable IBM InfoSphere Information Server is, I need to learn how to tune performance and scalability on the cloud. I am familiar with localized hardware, but on the cloud, I still have to do the work around it. In the beginning, we estimate the load and based on that, we put the hardware, but if there is continuous increase, I believe IBM also faces problems. Scalability needs to be improved because once the demand comes, you should be able to improve it, but for that, documentation on how to add hardware or resources to the software needs to be proper. I do not have much hands-on experience with that.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Azure Data Factory is a low code, no code platform, which is helpful."
"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."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"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."
"It is easy to deploy workflows and schedule jobs."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"IBM InfoSphere Information Server is stable."
"This solution is extremely flexible and scalable."
"Deploying the solution is straightforward for me."
"The integration with different technologies is the most valuable feature."
"Stability-wise, I rate the solution a ten out of ten."
"Over the years of working with IBM InfoSphere Information Server, I see basically the strength of the tool, capability, and load balancing, which I see is really good."
 

Cons

"The setup and configuration process could be simplified."
"We require Azure Data Factory to be able to connect to Google Analytics."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"When the record fails, it's tough to identify and log."
"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."
"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."
"There is a problem with the integration with third-party solutions, particularly with SAP."
"The initial setup is not very straightforward."
"IBM InfoSphere Information Server should be more scalable. It should have the option to change the configuration to run on a single, non-multiple node, or multi-threading processing."
"This solution would benefit from the engine being made more lightweight."
"We have decided to decrease the usage of metadata management because we did not see any significant advantages."
"Their technical support needs improvement."
"Unlike other tools, IBM tools do not provide much help from the internet, so additional support should be available."
"There are certain shortcomings in the cloud side of the solution, where improvements are required."
 

Pricing and Cost Advice

"The pricing model is based on usage and is not cheap."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"Pricing appears to be reasonable in my opinion."
"Product is priced at the market standard."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"The licensing cost of IBM InfoSphere Information Server depends on how many users there are."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Government
19%
Financial Services Firm
16%
Insurance Company
9%
Retailer
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise1
Large Enterprise4
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
What needs improvement with IBM InfoSphere Information Server?
As for utilizing the platform's metadata management feature, I have not worked on that feature yet, but personally, I have done that. To evaluate the effectiveness of IBM InfoSphere Information Ser...
What is your primary use case for IBM InfoSphere Information Server?
My usual use case for IBM InfoSphere Information Server is ETL, where we take data from one source to another data warehouse solution.
What advice do you have for others considering IBM InfoSphere Information Server?
Currently, IBM InfoSphere Information Server is deployed on-premises in my organization. Mostly it is on-premises only, but slowly things are changing towards pro-cloud. It will not be a public clo...
 

Also Known As

No data available
InfoSphere Information Server, IBM Information Server
 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Canadian National Railway Company, Chickasaw Nation Division of Commerce, Swedish Armed Forces, BG RCI, Janata Sahakari Bank Ltd., University of Arizona, Biogrid Australia
Find out what your peers are saying about Azure Data Factory vs. IBM InfoSphere Information Server and other solutions. Updated: February 2026.
881,733 professionals have used our research since 2012.