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Azure Data Factory vs IBM Db2 Warehouse on Cloud comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 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 Cloud Data Warehouse
2nd
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
92
Ranking in other categories
Data Integration (1st)
IBM Db2 Warehouse on Cloud
Ranking in Cloud Data Warehouse
15th
Average Rating
7.6
Reviews Sentiment
6.3
Number of Reviews
7
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 6.8%, down from 9.4% compared to the previous year. The mindshare of IBM Db2 Warehouse on Cloud is 0.8%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Azure Data Factory6.8%
IBM Db2 Warehouse on Cloud0.8%
Other92.4%
Cloud Data Warehouse
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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.
FM
Enhancing analytics with seamless data dumping and reliable support
Our primary use case is data storage and analytics The organization has decided to purchase a full stack solution from IBM due to positive responses, which helped them upgrade from the previous version. The data dumping into the raw zone and the feature of BigQuery is quite attractive. There…

Quotes from Members

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

Pros

"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."
"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS"
"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."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."
"The solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."
"The solution can scale very easily."
"The performance is okay as long as the volume of queries is not too high."
"It is stable when there is support from IBM."
"It will be MPP, so performance should improve."
"The way that it scales will help a lot of customers that are stuck with Netezza boxes that can't grow any larger.​"
 

Cons

"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"There is a problem with the integration with third-party solutions, particularly with SAP."
"Some of the optimization techniques are not scalable."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"It would be better if it had machine learning capabilities."
"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 thing we missed most was data update, but this is now available as of two weeks ago."
"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."
"Right now, we are implementing on ESX VMware 6.0. Support for this platform is poor. Also, one of the backup/recovery options is broken and IBM is not addressing the issue."
"There are some limitations in adding data files to table spaces, and improvements are needed for regional support."
"Containers get corrupted very easily. Restoring them using GPFS can result in a lot of issues."
"Ultimately, the product itself has challenges and we are not currently satisfied with the support, either."
"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."
 

Pricing and Cost Advice

"Understanding the pricing model for Data Factory is quite complex."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"The licensing cost is included in the Synapse."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"Product is priced at the market standard."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"The pricing model is based on usage and is not cheap."
"This is a cost-effective solution."
"If your going to go with warehouse DB/dashDB, use the cloud or Sailfish version."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
By reviewers
Company SizeCount
Small Business4
Large Enterprise3
 

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 advice do you have for others considering IBM Db2 Warehouse on Cloud?
Organizations of all sizes, especially those who are in need of powerful and elastic cloud data warehouse solutions that can help administrators maximize the efficiency of their data-based operatio...
What needs improvement with IBM Db2 Warehouse on Cloud?
There are some limitations in adding data files to table spaces, and improvements are needed for regional support.
What is your primary use case for IBM Db2 Warehouse on Cloud?
Our primary use case is data storage and analytics.
 

Also Known As

No data available
IBM dashDB
 

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
Copenhagen Business School, BPM Northwest, GameStop
Find out what your peers are saying about Azure Data Factory vs. IBM Db2 Warehouse on Cloud and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.