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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
5th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Data Integration (4th)
IBM Db2 Warehouse on Cloud
Ranking in Cloud Data Warehouse
16th
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 May 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.3%, down from 7.9% compared to the previous year. The mindshare of IBM Db2 Warehouse on Cloud is 2.1%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Azure Data Factory5.3%
IBM Db2 Warehouse on Cloud2.1%
Other92.6%
Cloud Data Warehouse
 

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.
FM
Database Engineer at Meezan Bank
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

"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"An excellent tool for pipeline orchestration."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"One of the most valuable features of Azure Data Factory is the drag-and-drop interface, which helps with workflow management because we can just drag any tables or data sources we need and, because of how easy it is to drag and drop, we can deliver things very quickly."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"I like that it's a monolithic data platform. This is why we propose these solutions."
"It is stable when there is support from IBM."
"The performance is okay as long as the volume of queries is not too high."
"Ease of migration from Netezza DB; IBM ported over all Netezza's functionality and made the warehouse DB/dashDB the best of breed of the two."
"It will be MPP, so performance should improve."
"Since my company is an IBM partner, it has enabled us to offer cloud data warehouse solutions on a 100% IBM stack."
"The way that it scales will help a lot of customers that are stuck with Netezza boxes that can't grow any larger.​"
"I like that the dashDB solution is built on DB2 technology, which means that you can use all the features of a DB2 database while outsourcing all the hardware and software maintenance."
"DashDB is a good product to work with and the extra cost you spend on performance, technical support and tools to work with is worth it."
 

Cons

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"I did not see any positive impact from Azure Data Factory overall."
"The solution needs to be more connectable to its own services."
"Data Factory's cost is too high."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load."
"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."
"When working with AWS, we have noticed that the difference between ADF and AWS is that AWS is more customer-focused. They're more responsive compared to any other company. ADF is not as good as AWS, but it should be. If AWS is ten out of ten, ADF is around eight out of ten. I think AWS is easier to understand from the GUI perspective compared to ADF."
"I would like to see improvements in backup and authentication. It needs the ability to increase the number of retained backups to more than 2 days."
"Containers get corrupted very easily. Restoring them using GPFS can result in a lot of issues."
"With dashDB, scalability and uptime need more improvement."
"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."
"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."
"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."
"Db2 is not a solution that I recommend. We have a lot of experience and we are not satisfied with the product or the support that we received."
"The support channels need to improve."
 

Pricing and Cost Advice

"The pricing model is based on usage and is not cheap."
"The licensing cost is included in the Synapse."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"I don't see a cost; it appears to be included in general support."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"Understanding the pricing model for Data Factory is quite complex."
"Pricing appears to be reasonable in my opinion."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"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
12%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
Financial Services Firm
15%
Construction Company
9%
Educational Organization
8%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
Large Enterprise57
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: April 2026.
893,244 professionals have used our research since 2012.