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 #35 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

16,078 Views
11,255 Comparison Views

92% willing to recommend

IBM InfoSphere Information ...

Read 9 IBM InfoSphere Information Server reviews

3,818 Views
2,596 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: November 2026).

Buyer's Guide

Azure Data Factory vs. IBM InfoSphere Information Server

November 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 (8th)

IBM InfoSphere Information ...

Ranking in Data Integration

35th

Average Rating

8.2

Reviews Sentiment

5.8

Number of Reviews

Ranking in other categories

Metadata Management (8th)

Mindshare comparison

As of November 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 4.4% 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.

Read full review

Quotes from Members

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

Pros

"So far, I'm quite happy with the solution overall."

"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."

"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."

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

"Since I have mentioned that I can use the drag-and-drop activities, by using that, Azure Data Factory is saving a lot of time, my organization has already been saving the time and generating more income with that."

"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."

"The most valuable feature is the ease in which you can create an ETL pipeline."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

More Azure Data Factory pros

"IBM InfoSphere Information Server is stable."

"Deploying the solution is straightforward for me."

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

"This solution is extremely flexible and scalable."

"Data connections, data partitioning, flexibility, and performance are the most valuable features."

"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."

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

"This solution has reduced the time it takes for ETL. We took an existing Teradata ETL application from three days to eight minutes."

More IBM InfoSphere Information Server pros

Cons

"The only thing that we're struggling with is increasing the competency of my team, so we think that the Microsoft documentation is too complicated."

"We have experienced some issues with the integration. This is an area that needs improvement."

"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."

"I find that Azure Data Factory is still maturing, so there are issues."

"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."

"I would like to see this time travel feature in Snowflake added to Azure Data Factory."

"Azure Data Factory can improve by having support in the drivers for change data capture."

"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."

More Azure Data Factory cons

"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."

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

"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."

"Customer Service: It's poor."

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

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

"Their technical support needs improvement."

Pricing and Cost Advice

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

"Pricing is comparable, it's somewhere in the middle."

"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."

"This is a cost-effective solution."

"Data Factory is affordable."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

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

"It's not particularly expensive."

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

Manufacturing Company

11%

Financial Services Firm

10%

Outsourcing Company

Computer Software Company

Financial Services Firm

14%

Construction Company

13%

Comms Service Provider

11%

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.

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...

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

Snowflake vs Azure Data Factory

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

More Azure Data Factory Competitors

Informatica PowerCenter vs IBM InfoSphere Information Server

Compared 10% 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 Data Services 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

October 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

November 2026

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