Azure Data Factory vs IBM InfoSphere Information Server comparison

Azure Data Factory vs. IBM InfoSphere Information Server

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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

5th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th)

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 September 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 5.5% 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

"Instead of individual people reviewing these files, we were able to automate the ingestion process, which saved a bunch of time and hours of repeated manual work."

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

"Azure Data Factory is a low code, no code platform, which is helpful."

"It works very well with Azure Data Factory to pull the records, parse them quickly and post them in the database and data warehouse."

"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."

"I value the integration capabilities with other platforms and software in Azure Data Factory the most."

"Data Factory's best features are simplicity and flexibility."

"Its integrability with the rest of the activities on Azure is most valuable."

More Azure Data Factory pros

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

"This solution is extremely flexible and scalable."

"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."

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

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

"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."

More IBM InfoSphere Information Server pros

Cons

"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."

"When you raise an issue, sometimes the people who are available are unfamiliar with that particular technology, so they have to route the issue to the concerned person."

"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."

"There are limitations when processing more than one GD file."

"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."

"The main challenge with implementing Azure Data Factory is that it processes data in batches, not near real-time. To achieve near real-time processing, we need to schedule updates more frequently, which can be an issue. Its interface needs to be lighter."

"The speed and performance need to be improved."

"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."

More Azure Data Factory cons

"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."

"Their technical support needs improvement."

"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."

"Customer Service: It's poor."

"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

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

"The price is fair."

"This is a cost-effective solution."

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

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

"Product is priced at the market standard."

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

"Data Factory is affordable."

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

Construction 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.

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...

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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

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

Compared 6% of the time

Oracle GoldenGate vs IBM InfoSphere Information Server

Compared 6% of the time

Oracle Data Integrator (ODI) vs IBM InfoSphere Information Server

Compared 3% of the time

More IBM InfoSphere Information Server Competitors

Product Reports

Azure Data Factory

Download Azure Data Factory product report

Data Integration

Download IBM InfoSphere Information Server product report

IBM InfoSphere Information Server 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

Azure Data Factory vs. IBM InfoSphere Information Server