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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
94
Ranking in other categories
Cloud Data Warehouse (2nd)
IBM InfoSphere Information ...
Ranking in Data Integration
32nd
Average Rating
8.2
Reviews Sentiment
5.8
Number of Reviews
9
Ranking in other categories
Metadata Management (6th)
 

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.8%, down from 9.7% compared to the previous year. The mindshare of IBM InfoSphere Information Server is 0.9%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.8%
IBM InfoSphere Information Server0.9%
Other96.3%
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

"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"Azure Data Factory is a low code, no code platform, which is helpful."
"The data flows were beneficial, allowing us to perform multiple transformations."
"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."
"We have been using drivers to connect to various data sets and consume data."
"The function of the solution is great."
"Its integrability with the rest of the activities on Azure is most valuable."
"It is beneficial that the solution is written with Spark as the back end."
"Reduces the loading and development time for Datawarehouse ETL."
"Deploying the solution is straightforward for me."
"Stability-wise, I rate the solution a ten out of ten."
"The integration with different technologies is the most valuable feature."
"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."
"IBM InfoSphere Information Server is stable."
"This solution is extremely flexible and scalable."
"Data connections, data partitioning, flexibility, and performance are the most valuable features."
 

Cons

"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"There is no built-in pipeline exit activity when encountering an error."
"The Microsoft documentation is too complicated."
"Azure Data Factory's pricing in terms of utilization could be improved."
"The deployment should be easier."
"It can improve from the perspective of active logging. It can provide active logging information."
"In the next release, it's important that some sort of scheduler for running tasks is added."
"There's space for improvement in the development process of the data pipelines."
"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."
"Unlike other tools, IBM tools do not provide much help from the internet, so additional support should be available."
"Heavy use of scratch disk which sometimes leads to failure."
"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."
"Customer Service: It's poor."
"There are certain shortcomings in the cloud side of the solution, where improvements are required."
 

Pricing and Cost Advice

"The licensing is a pay-as-you-go model, where you pay for what you consume."
"Data Factory is expensive."
"The pricing model is based on usage and is not cheap."
"I don't see a cost; it appears to be included in general support."
"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."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"The price you pay is determined by how much you use it."
"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
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Financial Services Firm
18%
Government
15%
Retailer
7%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
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?
We are using the on-premises version of IBM InfoSphere Information Server, but we feel that all new development is mainly for the cloud. We receive corrections of errors, but we do not see new func...
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?
We are about to change our platform from IBM AIX to SUSE Linux, as our whole platform is changing, so everyone should change from IBM to SUSE Linux. It would be very difficult for us to have a diff...
 

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: March 2026.
884,873 professionals have used our research since 2012.