Azure Data Factory vs IBM InfoSphere Information Server comparison

Why PeerSpot?

Microsoft and IBM are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while IBM is ranked #34 with an average rating of 8.0. Microsoft holds a 2.2% mindshare in DI, compared to IBM’s 0.8% 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 97 Azure Data Factory reviews

15,321 Views
10,725 Comparison Views

92% willing to recommend

IBM InfoSphere Information ...

Read 9 IBM InfoSphere Information Server reviews

3,493 Views
2,375 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: September 2026).

Buyer's Guide

Azure Data Factory vs. IBM InfoSphere Information Server

September 2026

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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

6th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (6th)

IBM InfoSphere Information ...

Ranking in Data Integration

34th

Average Rating

8.2

Reviews Sentiment

5.8

Number of Reviews

Ranking in other categories

Metadata Management (8th)

Mindshare comparison

As of October 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 5.1% compared to the previous year. The mindshare of IBM InfoSphere Information Server is 0.8%, down from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.2%
IBM InfoSphere Information Server	0.8%
Other	97.0%

Data Integration

Featured Reviews

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

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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

"We have used other ETL solutions in the past, and Azure Data Factory is the best one."

"The trigger scheduling options are decently robust."

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."

"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."

"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."

"The overall performance is quite good."

"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."

"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."

More Azure Data Factory pros

"Stability-wise, I rate the solution a ten out of ten."

"The initial IBM InfoSphere Information Server is straightforward and you can choose what type of installation you want, such as a customized installation, with clear-cut documentation that, if followed, works fine and the installation has not given us issues."

"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."

"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."

"Reduces the loading and development time for Datawarehouse ETL."

More IBM InfoSphere Information Server pros

Cons

"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."

"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."

"There's space for improvement in the development process of the data pipelines."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"The thing we missed most was data update, but this is now available as of two weeks ago."

"Areas for improvement would be the product's performance and its mapping of data flow."

"There is no built-in pipeline exit activity when encountering an error."

More Azure Data Factory cons

"Their technical support needs improvement."

"Heavy use of scratch disk which sometimes leads to failure."

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

"Customer Service: It's poor."

"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."

"We have decided to decrease the usage of metadata management because we did not see any significant advantages."

"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

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

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

"The cost is based on the amount of data sets that we are ingesting."

"Pricing appears to be reasonable in my opinion."

"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."

"ADF is cheaper compared to AWS."

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

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

11%

Manufacturing Company

Computer Software Company

Outsourcing Company

Financial Services Firm

15%

Construction Company

14%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

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

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.

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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...

See all answers

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...

See all answers

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...

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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.

See all answers

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...

See all answers

Comparisons

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Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

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Informatica PowerCenter vs IBM InfoSphere Information Server

Compared 9% of the time

IBM InfoSphere DataStage vs IBM InfoSphere Information Server

Compared 8% of the time

Oracle GoldenGate vs IBM InfoSphere Information Server

Compared 6% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs IBM InfoSphere Information Server

Compared 6% of the time

SAP Business Data Cloud vs IBM InfoSphere Information Server

Compared 2% of the time

More IBM InfoSphere Information Server Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

September 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 integrates seamlessly with both structured and unstructured data environments, offering advanced ETL capabilities and efficient data handling for large-scale enterprise applications.

IBM InfoSphere Information Server is designed for enterprise-level data integration with a focus on efficient ETL processes. It excels in moving data between sources and data warehouses, particularly valuable in sectors such as retail banking. Users leverage its robust Parallel Extender for improved processing efficiency and DataStage administration for comprehensive task management. However, areas like technical support and scalability require growth, especially for cloud-based deployments. While the Cloud Pak for Data enables acceleration on the cloud, the on-premises approach often remains tied to traditional hardware configurations.

What are the crucial features?

Parallel Extender: Enhances data processing efficiency.
DataStage Administration: Facilitates comprehensive management of ETL tasks.
Change Capture: Monitors and tracks data modifications effectively.
Handling Partitioned Databases: Enables efficient data management across partitions.
Metadata Management: Despite limitations, offers basic insights and tracking.

What benefits or ROI should be evaluated?

Cloud Pak for Data: Accelerates data transformation in cloud environments.
ETL Capabilities: Provides robust extraction, transformation, and loading processes.
Versatility: Handles both structured and unstructured data efficiently.
Bulk Loads Parameter Sets: Enhances loading efficiency with bulk operations.

IBM InfoSphere Information Server is widely implemented in industries that require heavy data transformation, such as retail and financial services. Its robust ETL processes are essential for moving critical data between systems, ensuring streamlined data flow and integration across various platforms.

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

September 2026

Free Report: Azure Data Factory vs. IBM InfoSphere Information Server

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