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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:
 

ROI

Sentiment score
6.4
Azure Data Factory offers significant ROI, efficiency, and cost savings, with users highlighting benefits in data integration and migration.
Sentiment score
6.5
IBM Cloud Pak for Data helps large enterprises improve data quality, boosting AI processes and enhancing decision-making productivity.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
Data Engineer at Vthinktechnologies
I have seen a return on investment, as one of the returns on ROI is better performance in analysis and data collection from multiple sources, which has enabled us to gain insights to make data-driven decisions.
Operations Manager at IQVIA
 

Customer Service

Sentiment score
6.3
Azure Data Factory support is generally satisfactory, with responsive assistance and strong community resources enhancing user satisfaction.
Sentiment score
7.7
IBM Cloud Pak for Data's support is responsive and available 24/7, despite some delays due to system complexity.
The technical support from Microsoft is rated an eight out of ten.
Chief Analytics Officer at Idiro Analytics
The technical support is responsive and helpful
Sr. Technical Architect at Hexaware Technologies Limited
The technical support for Azure Data Factory is generally acceptable.
Solution Architect at Mercedes-Benz AG
Cloud Pak is a complicated system, and it's often difficult to find the right resource in IBM to help with specific issues.
Data asset management engineer at a tech services company with 1-10 employees
They are available 24/7 and reachable via email, chat, or live chat or through the phone.
Operations Manager at IQVIA
I would rate IBM's support at about a seven or eight out of ten because we have good support coverage owing to our long association with IBM.
EDW Manager at a university with 1,001-5,000 employees
 

Scalability Issues

Sentiment score
7.4
Azure Data Factory offers scalable cloud-based solutions for diverse operations, despite some third-party integration limitations and use case challenges.
Sentiment score
7.4
IBM Cloud Pak for Data is praised for impressive scalability and compatibility, despite being resource-intensive, with ratings mostly 8-10.
Azure Data Factory is highly scalable.
Chief Analytics Officer at Idiro Analytics
The scalability of IBM Cloud Pak for Data is impressive, as it grows with my organization's needs.
Operations Manager at IQVIA
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is considered highly stable and reliable, though minor issues can occur, mostly in development environments.
Sentiment score
7.5
IBM Cloud Pak for Data is generally stable and well-rated, with users emphasizing scalability despite minor tool integration concerns.
The solution has a high level of stability, roughly a nine out of ten.
Chief Analytics Officer at Idiro Analytics
 

Room For Improvement

Azure Data Factory needs better integration, UI, documentation, data handling, pricing transparency, real-time processing, connectivity, and scheduling.
IBM Cloud Pak for Data needs better integration, support, features, and pricing to attract small businesses and simplify adoption.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Chief Analytics Officer at Idiro Analytics
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
Sr. Technical Architect at Hexaware Technologies Limited
There is a problem with the integration with third-party solutions, particularly with SAP.
Solution Architect at Mercedes-Benz AG
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.
Data asset management engineer at a tech services company with 1-10 employees
Pricing is something that could be reduced, especially for small business enterprises to afford IBM Cloud Pak for Data.
Operations Manager at IQVIA
I do not know if Cognos has all the features that users are looking for since we provide it as our standard and do not maintain infrastructure for other tools.
EDW Manager at a university with 1,001-5,000 employees
 

Setup Cost

Azure Data Factory's pricing is pay-as-you-go, with costs based on usage, offering competitive and cost-effective solutions.
IBM Cloud Pak for Data's high pricing and complexity make it more suitable for large enterprises than smaller companies.
The pricing is cost-effective.
Chief Analytics Officer at Idiro Analytics
It is considered cost-effective.
Sr. Technical Architect at Hexaware Technologies Limited
The setup cost is very expensive.
Data asset management engineer at a tech services company with 1-10 employees
The amount of data compared to the price is reasonable, and the setup was quite straightforward.
Operations Manager at IQVIA
 

Valuable Features

Azure Data Factory offers scalable ETL processes with easy integration, user-friendly interface, and strong orchestration, security, and automation features.
IBM Cloud Pak for Data excels with data virtualization, low-code navigation, robust security, and efficient data integration and collaboration.
It connects to different sources out-of-the-box, making integration much easier.
Sr. Technical Architect at Hexaware Technologies Limited
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Data Engineer at Vthinktechnologies
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
Director at a computer software company with 1,001-5,000 employees
From there, I can work my way into a more granular level, applying all of that information on top of my actual data to understand what my data looks like, where it came from, and where it went wrong, managing it throughout the cycle.
Data asset management engineer at a tech services company with 1-10 employees
The benefits of choosing IBM Cognos, in addition to saving on cost, include having institutional knowledge about maintaining this infrastructure and enough people who have developed on Cognos in the past, which creates comfort in its use.
EDW Manager at a university with 1,001-5,000 employees
IBM Cloud Pak for Data is an all-in-one cloud-native data and AI platform that centralizes everything to one single platform, making it easy for viewing our data.
Operations Manager at IQVIA
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
IBM Cloud Pak for Data
Ranking in Data Integration
23rd
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
15
Ranking in other categories
Data Virtualization (3rd)
 

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 Cloud Pak for Data is 1.3%, down from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.2%
IBM Cloud Pak for Data1.3%
Other95.5%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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.
DJ
Operations Manager at IQVIA
Centralized data analysis has improved collaboration and delivers faster data driven decisions
The best features IBM Cloud Pak for Data offers include low-code or no-code options, which can be used by any technical expertise level. The user interface is very intuitive and easy to customize and navigate for any user, making the learning curve smooth. IBM Cloud Pak for Data is an all-in-one cloud-native data and AI platform that centralizes everything to one single platform, making it easy for viewing our data. It connected with our product for integration with the cloud and helped us enable all of our data users to collaborate from a single unified interface that supports many services designed to work together. I appreciate the low-code no-code feature for its visualization and reporting capabilities, which are very helpful in analyzing insights and making data-driven decisions. IBM Cloud Pak for Data has positively impacted my organization by saving a lot of time by predicting outcomes faster using a platform built with data fabric architecture. It has also enabled us to easily collect, organize, and analyze data, no matter where it is, thereby gaining insights we use to make data-driven decisions easily. It eliminates manual cataloging, which saves time and cost. When comparing it with our previous solution, we have been able to save approximately 70% of our time monthly. We have also been able to make data-driven and concrete decisions more easily compared to our previous solution. Our security has also been strengthened because IBM Cloud Pak for Data provides robust security features that protect our data.
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
7%
Financial Services Firm
27%
Manufacturing Company
10%
Computer Software Company
8%
Government
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
By reviewers
Company SizeCount
Small Business7
Large Enterprise11
 

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 is your experience regarding pricing and costs for IBM Cloud Pak for Data?
The pricing and setup cost are handled by a different procurement team. Our IT procurement team is centralized, so licensing and the actual cost of the software are taken care of by a different tea...
What needs improvement with IBM Cloud Pak for Data?
I do not know if Cognos has all the features that users are looking for since we provide it as our standard and do not maintain infrastructure for other tools.
What is your primary use case for IBM Cloud Pak for Data?
The main use case for IBM Cognos is for business intelligence and reporting.
 

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: December 2025.
880,844 professionals have used our research since 2012.