Try our new research platform with insights from 80,000+ expert users

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
6.8
Number of Reviews
94
Ranking in other categories
Data Integration (3rd)
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 March 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.4%, down from 8.5% compared to the previous year. The mindshare of IBM Db2 Warehouse on Cloud is 1.8%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Azure Data Factory5.4%
IBM Db2 Warehouse on Cloud1.8%
Other92.8%
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

"Azure Data Factory was not difficult to deploy because it is a small area, so we completed it very quickly."
"The most important feature is that it can help you do the multi-threading concepts."
"I like the basic features like the data-based pipelines."
"From my experience so far, the best feature is the ability to copy data to any environment."
"The most valuable part of this product is the ease of use, as it is easy to use and rather intuitive, and because it is easy to use, you can do things with it easily, making your work easier and therefore more valuable."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"It is beneficial that the solution is written with Spark as the back end."
"It makes it easy to collect data from different sources."
"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."
"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."
"The way that it scales will help a lot of customers that are stuck with Netezza boxes that can't grow any larger.​"
"Since my company is an IBM partner, it has enabled us to offer cloud data warehouse solutions on a 100% IBM stack."
"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 is stable when there is support from IBM."
"One of the most amazing features of dashDB is how it uses compression to get results in lighting speed."
 

Cons

"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
"From my perspective, the pricing seems like it could be more user-friendly."
"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."
"I have not found any real shortcomings within the product."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"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."
"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."
"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."
"With dashDB, scalability and uptime need more improvement."
"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."
"I would rate the level of dashDB support 3.5/5. While they are very knowledgeable in many areas, you can still struggle to get the correct resolution."
"There are some limitations in adding data files to table spaces, and improvements are needed for regional support."
 

Pricing and Cost Advice

"ADF is cheaper compared to AWS."
"I would rate Data Factory's pricing nine out of ten."
"The pricing is a bit on the higher end."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"Pricing is comparable, it's somewhere in the middle."
"Understanding the pricing model for Data Factory is quite complex."
"The price is fair."
"If your going to go with warehouse DB/dashDB, use the cloud or Sailfish version."
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
884,933 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
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 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: March 2026.
884,933 professionals have used our research since 2012.