Azure Data Factory vs IBM Db2 Warehouse comparison

Microsoft and IBM are both solutions in the Cloud Data Warehouse category. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 81% of IBM users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

14,099 Views
2,538 Comparison Views

92% willing to recommend

IBM Db2 Warehouse

Read 12 IBM Db2 Warehouse reviews

2,550 Views
2,015 Comparison Views

81% willing to recommend

Azure Data Factory

IBM Db2 Warehouse

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and IBM Db2 Warehouse based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: August 2026).

Buyer's Guide

Cloud Data Warehouse

August 2026

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Helped 909,725 peers since 2012

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

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Integration (5th), Cloud Data Warehouse (7th)

IBM Db2 Warehouse

Average Rating

7.8

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Data Warehouse (13th)

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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Sherpard Muzuva

Senior Technical Manager at SYSTEMS INTEGRATED LTD (SYMPHONY)

Advanced features enhance business intelligence, but complex management calls for improved user guidance

While my experience with IBM Db2 Warehouse is somewhat limited, when compared to other databases such as Oracle, there are areas for improvement. They need to enhance the database to make it more user-friendly and easier to master. They should implement a more comprehensive graphical user interface with additional features. For instance, when users encounter problems, the system should provide better guidelines and troubleshooting directions, except for hardware-related issues. They need to implement tools that would help users perform basic troubleshooting rather than solely relying on support. Other databases have features where users can investigate specific issues using error codes. From my experience, many minor issues could be resolved before escalating to support.

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Quotes from Members

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

Pros

"I am one hundred percent happy with the stability."

"We have used other ETL solutions in the past, and Azure Data Factory is the best one."

"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."

"We use the solution to move data from on-premises to the cloud."

"Powerful but easy-to-use and intuitive."

"Data Factory's best features are simplicity and flexibility."

"The overall architecture has been very valuable to us, as it has allowed us to scale up pretty rapidly."

"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."

More Azure Data Factory pros

"The solution is stable."

"If you have good people designing how the data is stored, it's a marvelous tool."

"It can be mounted on the cloud, which is a huge plus. If the client, for example, starts small with on-premise deployment and then it rapidly needs to grow, we can transfer this to the cloud easily."

"The standout feature of IBM Db2 Warehouse, which is particularly valuable for large enterprises, is its ability to handle big data."

"It's easy and practical to use."

"It can scale effectively as long as resources are available."

"The most valuable features of IBM Db2 Warehouse include its availability, easy integration, ability to deal with a large size of data, excellent performance with no delays, powerful security mechanisms, and effective support."

"The initial setup was really easy; it's Docker compliant, you just pull the image from the IBM repository and that's it, and the deployment must have taken less than an hour, making it really fast to have it completely working."

More IBM Db2 Warehouse pros

Cons

"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."

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

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."

"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."

"Data Factory's performance during heavy data processing isn't great."

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."

"When the record fails, it's tough to identify and log."

"I find that Azure Data Factory is still maturing, so there are issues."

More Azure Data Factory cons

"Lacks sufficient documentation and particularly in Spanish."

"IBM Db2 Warehouse needs to improve its interface."

"There should be more material available for training and training should be free."

"The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting."

"Responding to support tickets takes a lot of time. It can range from two to four days, even for critical issues."

"On a scale of one to ten, I would rate the technical support as a five. It is fairly bad."

"It takes a long time to have a new version or release, similar to Oracle."

"I previously used DataStage, which I think is better than InfoSphere Warehouse."

More IBM Db2 Warehouse cons

Pricing and Cost Advice

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

"I would not say that this product is overly expensive."

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

"Product is priced at the market standard."

"The pricing model is based on usage and is not cheap."

"Pricing appears to be reasonable in my opinion."

"The cost is based on the amount of data sets that we are ingesting."

"The licensing cost is included in the Synapse."

More Azure Data Factory pricing and cost advice

"In a traditional on-prem database, in a data warehouse, the solution is probably on the expensive side."

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909,725 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

24%

Construction Company

11%

Manufacturing Company

Comms Service Provider

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	5
Midsize Enterprise	3
Large Enterprise	5

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 is your experience regarding pricing and costs for IBM Db2 Warehouse?

The pricing for medium and large environments is almost the same as Oracle. I rate the pricing as six out of ten.

See all answers

What needs improvement with IBM Db2 Warehouse?

See all answers

What is your primary use case for IBM Db2 Warehouse?

The main advantages of IBM Db2 Warehouse become apparent when dealing with business intelligence applications. I worked with it when it was installed for one of our customers, a utilities company, ...

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 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Snowflake vs IBM Db2 Warehouse

Compared 11% of the time

BigQuery vs IBM Db2 Warehouse

Compared 9% of the time

Amazon Redshift vs IBM Db2 Warehouse

Compared 8% of the time

Oracle Exadata vs IBM Db2 Warehouse

Compared 8% of the time

Magnitude vs IBM Db2 Warehouse

Compared 7% of the time

More IBM Db2 Warehouse Competitors

Product Reports

Buyer's Guide

Azure Data Factory

August 2026

Download Azure Data Factory product report

Buyer's Guide

IBM Db2 Warehouse

August 2026

Download IBM Db2 Warehouse product report

Also Known As

No data available

InfoSphere Warehouse, IBM InfoSphere Warehouse

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 provides scalable and efficient data handling, offering rapid data processing, excellent integration capabilities, and strong security. Its compatibility with cloud environments and robust analytics make it ideal for enterprises requiring high-performance transaction processing.

IBM Db2 Warehouse is recognized for its big data scalability and fast response times. Its support for ETL processes and robust security measures ensures consistent data handling. Easy installation and a powerful analytics engine facilitate forecasting, making it practical for high-volume transactions. It supports Windows and Linux, offering a flexible yet resilient environment. However, improvements are needed in separating compute from storage, interface usability, and Spanish documentation. Users may experience delays in support response and challenges with publication and backup issues, highlighting the need for enhanced training resources and user-friendly troubleshooting tools. Though related to Oracle, IBM Db2 Warehouse may benefit from improved user guidance and online resources.

What are the standout features of IBM Db2 Warehouse?

Scalability: Effectively handles big data volumes.
Integration: Seamlessly works with multiple platforms, including IBM Cognos.
Analytics Engine: Robust tools support forecasting and advanced analytics.
Security: Offers strong security measures for data protection.
Cloud Compatibility: Deployable on IBM Cloud with ease.

What benefits and ROI should users consider?

Data Processing Speed: Fast response boosts efficiency.
Reliability: High volume transactions are managed efficiently.
Analytics Power: Enhances decision-making with data analytics capabilities.
Deployment Flexibility: Supports Windows and Linux systems.

IBM Db2 Warehouse is implemented across industries for data warehousing, reporting, and analytics, notably benefiting businesses focusing on utilities usage prediction and growth analysis. Its integration with IBM Cognos enhances report generation, while its support for star or snowflake schemas optimizes high-volume data management, providing a solid foundation for data-driven decision-making in business intelligence applications.

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

Alameda County Social Services Agency, Sui Southern Gas Company Limited

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