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Azure Data Factory vs IBM Cloud Pak for Data 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
1st
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Cloud Data Warehouse (2nd)
IBM Cloud Pak for Data
Ranking in Data Integration
24th
Average Rating
7.8
Reviews Sentiment
6.5
Number of Reviews
13
Ranking in other categories
Data Virtualization (3rd)
 

Mindshare comparison

As of June 2025, in the Data Integration category, the mindshare of Azure Data Factory is 8.4%, down from 12.3% compared to the previous year. The mindshare of IBM Cloud Pak for Data is 1.9%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
Michelle Leslie - PeerSpot reviewer
Starts strong with data management capabilities but needs a demo database
What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

Quotes from Members

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

Pros

"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"The user interface is very good. It makes me feel very comfortable when I am using the tool."
"Allows more data between on-premises and cloud solutions"
"The solution is okay."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."
"DataStage allows me to connect to different data sources."
"Its data preparation capabilities are highly valuable."
"I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography."
"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."
"You can model the data there, connect the data models with the business processes and create data lineage processes."
"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."
"IBM Watson Catalog and data pipelines are the most valuable features of the solution."
 

Cons

"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"The speed and performance need to be improved."
"The solution needs to be more connectable to its own services."
"Data Factory's monitorability could be better."
"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."
"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."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"The Microsoft documentation is too complicated."
"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."
"The solution's user experience is an area that has room for improvement."
"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."
"The technical support could be a little better."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem."
"The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one."
"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."
 

Pricing and Cost Advice

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"The pricing model is based on usage and is not cheap."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"The licensing cost is included in the Synapse."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"ADF is cheaper compared to AWS."
"Cloud Pak's cost is a little high."
"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."
"The solution's pricing is competitive with that of other vendors."
"It's quite expensive."
"I think that this product is too expensive for smaller companies."
"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."
"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."
"The solution is expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
30%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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 do you like most about IBM Cloud Pak for Data?
DataStage allows me to connect to different data sources.
What is your experience regarding pricing and costs for IBM Cloud Pak for Data?
The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.
What needs improvement with IBM Cloud Pak for Data?
What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data...
 

Also Known As

No data available
Cloud Pak for Data
 

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
Qatar Development Bank, GuideWell, Skanderborg Music Festival
Find out what your peers are saying about Azure Data Factory vs. IBM Cloud Pak for Data and other solutions. Updated: June 2025.
859,579 professionals have used our research since 2012.