Azure Data Factory vs IBM Db2 Warehouse on Cloud comparison

Why PeerSpot?

Microsoft and IBM are both solutions in the Cloud Data Warehouse category. Microsoft is ranked #7 with an average rating of 8.0, while IBM is ranked #16 with an average rating of 8.0. Microsoft holds a 5.2% mindshare in CDW, compared to IBM’s 2.0% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 85% of IBM users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

14,793 Views
2,663 Comparison Views

92% willing to recommend

IBM Db2 Warehouse on Cloud

Read 7 IBM Db2 Warehouse on Cloud reviews

1,563 Views
797 Comparison Views

85% willing to recommend

Azure Data Factory

IBM Db2 Warehouse on Cloud

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 18, 2024

IBM Db2 Warehouse on Cloud and Azure Data Factory compete in the cloud data management and integration category. Azure Data Factory may have the upper hand in data integration due to its extensive capabilities and scalability, whereas IBM Db2 Warehouse on Cloud excels in analytics.

Features: IBM Db2 Warehouse on Cloud includes powerful analytics capabilities, built-in machine learning, and seamless cloud integration. Azure Data Factory offers comprehensive data integration capabilities, supports a wide range of data sources, and efficiently orchestrates data pipelines.

Room for Improvement: IBM Db2 Warehouse on Cloud could improve in providing a more intuitive user interface, expanding real-time analytics features, and enhancing support for diverse data sources. Azure Data Factory might benefit from simplifying deployment processes, enhancing initial setup guidance, and expanding its monitoring and debugging tools to improve usability.

Ease of Deployment and Customer Service: IBM Db2 Warehouse on Cloud offers automated scaling with a straightforward deployment process and is praised for its responsive customer service. Azure Data Factory provides flexible deployment options and extensive support from Microsoft's network, though it may require more configuration from users.

Pricing and ROI: IBM Db2 Warehouse on Cloud is competitively priced to prioritize analytics ROI, making it appealing to companies focusing on data insights. Azure Data Factory's pricing reflects its broad integration capabilities, with ROI highlighted by its scalability and integration flexibility, making it a strong choice for complex data orchestration needs.

To learn more, read our detailed Azure Data Factory vs. IBM Db2 Warehouse on Cloud Report (Updated: September 2026).

Buyer's Guide

Azure Data Factory vs. IBM Db2 Warehouse on Cloud

September 2026

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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

7th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (5th)

IBM Db2 Warehouse on Cloud

Ranking in Cloud Data Warehouse

16th

Average Rating

7.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.2%, down from 6.8% compared to the previous year. The mindshare of IBM Db2 Warehouse on Cloud is 2.0%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	5.2%
IBM Db2 Warehouse on Cloud	2.0%
Other	92.8%

Cloud Data Warehouse

Featured Reviews

Kunal Das

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.

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FarhanFarhan

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…

Read full review

Quotes from Members

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

Pros

"Its integrability with the rest of the activities on Azure is most valuable."

"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."

"The most valuable features are data transformations."

"I like the basic features like the data-based pipelines."

"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"The solution is okay."

"The support for SAP services and databases, specifically SAP HANA, has been a game-changer for us."

"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."

More Azure Data Factory pros

"It is stable when there is support from IBM."

"It will be MPP, so performance should improve."

"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."

"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."

"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."

"One of the most amazing features of dashDB is how it uses compression to get results in lighting speed."

More IBM Db2 Warehouse on Cloud pros

Cons

"Some known bugs and issues with Azure Data Factory could be rectified."

"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."

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."

"But, I feel that if the usage extends beyond a certain threshold, it will start getting expensive."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"There aren't many third-party extensions or plugins available in the solution."

"The only challenge with Azure Data Factory is its exception-handling mechanism."

"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."

More Azure Data Factory cons

"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."

"Ultimately, the product itself has challenges and we are not currently satisfied with the support, either."

"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."

"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."

"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."

"With dashDB, scalability and uptime need more improvement."

"The support channels need to improve."

More IBM Db2 Warehouse on Cloud cons

Pricing and Cost Advice

"The licensing cost is included in the Synapse."

"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."

"This is a cost-effective solution."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

"Understanding the pricing model for Data Factory is quite complex."

"The price you pay is determined by how much you use it."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

More Azure Data Factory pricing and cost advice

"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

11%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

16%

Comms Service Provider

12%

Outsourcing Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

By reviewers
Company Size	Count
Small Business	4
Large Enterprise	3

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.

See all answers

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...

See all answers

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...

See all answers

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...

See all answers

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.

See all answers

What is your primary use case for IBM Db2 Warehouse on Cloud?

Our primary use case is data storage and analytics.

See all answers

Comparisons

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Amazon Redshift vs IBM Db2 Warehouse on Cloud

Compared 18% of the time

Snowflake vs IBM Db2 Warehouse on Cloud

Compared 14% of the time

Oracle Exadata vs IBM Db2 Warehouse on Cloud

Compared 6% of the time

Microsoft Parallel Data Warehouse vs IBM Db2 Warehouse on Cloud

Compared 6% of the time

Amazon EMR vs IBM Db2 Warehouse on Cloud

Compared 4% of the time

More IBM Db2 Warehouse on Cloud Competitors

Product Reports

Buyer's Guide

Azure Data Factory

September 2026

Download Azure Data Factory product report

Buyer's Guide

Cloud Data Warehouse

September 2026

Download IBM Db2 Warehouse on Cloud product report

Also Known As

No data available

IBM dashDB

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

IBM Db2 Warehouse on Cloud is an advanced data warehouse offering that provides flexible deployment options and seamless integration, crucial for dynamic data-driven operations in today's market.

IBM Db2 Warehouse on Cloud delivers robust performance and scalability, making it ideal for handling high data volumes with ease. Its cloud-native architecture ensures consistent reliability, catering to industries with ever-evolving demands for data analytics. Users benefit from a pay-as-you-go model, eliminating the need to maintain physical infrastructure while benefiting from continuous updates and improvements. The platform's robust capabilities support diverse and adaptable analytic workloads, providing critical business insights at speed.

What are the key features of IBM Db2 Warehouse on Cloud?

Elastic Scaling: Automatically adjusts resources to meet current workloads, optimizing performance and cost.
Multitenancy Support: Ensures data isolation and security for multiple users within a single architecture.
Data Virtualization: Integrates data across sources without physical movement, maintaining data quality and accessibility.
In-database Analytics: Enables advanced analytics and machine learning directly within the data warehouse, enhancing data processing efficiency.

What benefits or ROI should users consider when evaluating IBM Db2 Warehouse on Cloud?

Cost Efficiency: Reduces expenses related to hardware purchase and maintenance, allowing organizations to focus on strategic tasks.
Scalability: Provides the ability to scale resources up or down based on business needs, optimizing investment returns.
Time Savings: Facilitates faster data processing and retrieval, enabling quicker decision-making processes.

IBM Db2 Warehouse on Cloud is implemented across industries like finance, healthcare, and retail, where complex data environments and large-scale analytics demand robust and flexible architectures. Its ability to handle diverse data sets and provide actionable insights swiftly makes it indispensable in sectors where timely data interpretation is critical to operations and strategy development.

IBM

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

Buyer's Guide

Azure Data Factory vs. IBM Db2 Warehouse on Cloud

September 2026

Free Report: Azure Data Factory vs. IBM Db2 Warehouse on Cloud

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