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Azure Data Factory vs IBM Db2 Warehouse on Cloud comparison

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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
8th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
97
Ranking in other categories
Data Integration (6th)
IBM Db2 Warehouse on Cloud
Ranking in Cloud Data Warehouse
18th
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 November 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.0%, down from 6.3% compared to the previous year. The mindshare of IBM Db2 Warehouse on Cloud is 2.2%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Azure Data Factory5.0%
IBM Db2 Warehouse on Cloud2.2%
Other92.8%
Cloud Data Warehouse
 

Featured Reviews

Kunal Das - PeerSpot reviewer
Test Engineer at Happiest Minds Technologies
Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling
If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.
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

"We have been using drivers to connect to various data sets and consume data."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"It is easy to deploy workflows and schedule jobs."
"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"Azure Data Factory is a good tool."
"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."
"The most valuable feature of this solution is that it allows more data between on-premises and cloud solutions."
"Azure Data Factory is a very easy to use tool."
"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."
"It will be MPP, so performance should improve."
"One of the most amazing features of dashDB is how it uses compression to get results in lighting speed."
"It is stable when there is support from IBM."
"The way that it scales will help a lot of customers that are stuck with Netezza boxes that can't grow any larger.​"
"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."
"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

"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"It would be better if it had machine learning capabilities."
"The deployment should be easier."
"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"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."
"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."
"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."
"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."
"The support channels need to improve."
"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."
 

Pricing and Cost Advice

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"The price is fair."
"This is a cost-effective solution."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"Understanding the pricing model for Data Factory is quite complex."
"The cost is based on the amount of data sets that we are ingesting."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."
"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
Manufacturing Company
11%
Financial Services Firm
10%
Outsourcing Company
8%
Computer Software Company
7%
Financial Services Firm
16%
Comms Service Provider
12%
Construction Company
9%
Outsourcing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise64
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 2026.
920,929 professionals have used our research since 2012.