Azure Data Factory vs IBM InfoSphere Information Server comparison

Microsoft and IBM are both solutions in the Data Integration category. Microsoft is ranked #3 with an average rating of 8.2, while IBM is ranked #29 with an average rating of 8.0. Microsoft holds a 3.2% mindshare in DI, compared to IBM’s 1.0% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Azure Data Factory

Read 93 Azure Data Factory reviews

11,197 Views
7,838 Comparison Views

92% willing to recommend

IBM InfoSphere Information ...

Read 8 IBM InfoSphere Information Server reviews

1,528 Views
1,161 Comparison Views

100% willing to recommend

Azure Data Factory

IBM InfoSphere Information ...

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Executive SummaryUpdated on Dec 19, 2024

IBM InfoSphere Information Server and Azure Data Factory compete in the data integration and management space. Azure Data Factory appears to have the upper hand due to its comprehensive features and overall value.

Features: IBM InfoSphere Information Server offers data integration capabilities, data quality tools, and metadata management. Azure Data Factory provides cloud data integration, supports a vast range of data sources, and offers scalable orchestration tools.

Room for Improvement: IBM InfoSphere Information Server could benefit from simplification in deployment, enhancing user experience, and reducing resource intensity. Azure Data Factory may enhance its integration with certain on-premise systems, improve pipeline monitoring tools, and offer more advanced data transformation capabilities.

Ease of Deployment and Customer Service: IBM InfoSphere Information Server's deployment is complex but offers strong enterprise support. Azure Data Factory provides smoother cloud-based deployment with robust Microsoft support.

Pricing and ROI: IBM InfoSphere Information Server has higher initial setup costs, impacting early-stage ROI but offering long-term value for on-prem solutions. Azure Data Factory's pay-as-you-go pricing model provides quicker ROI, aligning costs with growth.

To learn more, read our detailed Azure Data Factory vs. IBM InfoSphere Information Server Report (Updated: December 2025).

Buyer's Guide

Azure Data Factory vs. IBM InfoSphere Information Server

December 2025

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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

Ranking in other categories

Cloud Data Warehouse (2nd)

IBM InfoSphere Information ...

Ranking in Data Integration

29th

Average Rating

8.2

Reviews Sentiment

5.8

Number of Reviews

Ranking in other categories

Metadata Management (6th)

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.2%, down from 10.0% compared to the previous year. The mindshare of IBM InfoSphere Information Server is 1.0%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Azure Data Factory	3.2%
IBM InfoSphere Information Server	1.0%
Other	95.8%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

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.

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MOHAMMAD-IQBAL

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.

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Quotes from Members

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

Pros

"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."

"The security of the agent that is installed on-premises is very good."

"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."

"It's extremely consistent."

"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."

"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."

"We use the solution to move data from on-premises to the cloud."

"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."

More Azure Data Factory pros

"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."

"The integration with different technologies is the most valuable feature."

"This solution is extremely flexible and scalable."

"IBM InfoSphere Information Server is stable."

Cons

"The pricing model should be more transparent and available online."

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"The deployment should be easier."

"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."

"The support and the documentation can be improved."

"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."

"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."

"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."

More Azure Data Factory cons

"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."

"Their technical support needs improvement."

"This solution would benefit from the engine being made more lightweight."

"There are certain shortcomings in the cloud side of the solution, where improvements are required."

"Unlike other tools, IBM tools do not provide much help from the internet, so additional support should be available."

Pricing and Cost Advice

"This is a cost-effective solution."

"The pricing is a bit on the higher end."

"It's not particularly expensive."

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

"Understanding the pricing model for Data Factory is quite complex."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"The price you pay is determined by how much you use it."

More Azure Data Factory pricing and cost advice

"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

Government

18%

Financial Services Firm

16%

Insurance Company

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	19
Large Enterprise	57

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	1
Large Enterprise	3

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.

See all answers

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...

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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...

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What needs improvement with IBM InfoSphere Information Server?

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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.

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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...

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Comparisons

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Compared 7% of the time

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Compared 6% of the time

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Compared 4% of the time

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Compared 19% of the time

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Compared 13% of the time

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Compared 8% of the time

Qlik Replicate vs IBM InfoSphere Information Server

Compared 6% of the time

IBM Watson Knowledge Catalog vs IBM InfoSphere Information Server

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Product Reports

Buyer's Guide

Azure Data Factory

January 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

January 2026

IBM InfoSphere Information Server report

Download IBM InfoSphere Information Server product report

Also Known As

No data available

InfoSphere Information Server, IBM Information Server

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

IBM InfoSphere Information Server is a market-leading data integration platform which includes a family of products that enable you to understand, cleanse, monitor, transform, and deliver data, as well as to collaborate to bridge the gap between business and IT. InfoSphere Information Server provides massively parallel processing (MPP) capabilities to deliver a highly scalable and flexible integration platform that handles a variety of data volumes (big, small, and everything in between).

IBM

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

Buyer's Guide

Azure Data Factory vs. IBM InfoSphere Information Server

December 2025

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