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Azure Data Factory vs ETL Solutions Transformation Manager comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 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 Data Integration
5th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Cloud Data Warehouse (7th)
ETL Solutions Transformatio...
Ranking in Data Integration
53rd
Average Rating
9.0
Reviews Sentiment
6.8
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.6% compared to the previous year. The mindshare of ETL Solutions Transformation Manager is 1.0%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.3%
ETL Solutions Transformation Manager1.0%
Other96.7%
Data Integration
 

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.
Vijayraj Amin - PeerSpot reviewer
Global Growth Strategist at MAIORA
User-friendly and accessible for anyone with computer knowledge and logical thinking
There is room for improvement in the solution's visualization tool. Currently, it provides basic reports and the ability to create graphs and dashboards, but I'm looking forward to more robust analytics. The plan is to enhance this feature in 2024, around Q2 or Q3, which would save us from relying on external tools like Power BI for insights.

Quotes from Members

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

Pros

"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."
"Azure Data Factory is a very easy to use ETL tool for loading and transforming data from one location to another."
"It's a good tool, a good product that does what it's supposed to do well, which is ingesting data from a source to your target, to another cloud, to another source."
"The solution can scale very easily."
"It is easy to integrate."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"It is easy to deploy workflows and schedule jobs."
"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."
"It is a reliable solution."
"Transformation Manager is the backbone of every data pipeline these days because the solution has been on the market for 20 to 30 years, and we use it for various industries, including financial services, manufacturing, healthcare, etc."
"It is among the best, even if not widely known."
"Back in the day, we could only get reports and analyze what happened after the fact, but today now we can generate real-time insights. Transformation Manager feeds your data science projects. We generate models and then give them to the clients, so they can come up with real-time predictions and recommendations in addition to reporting."
 

Cons

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"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."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"Some of the optimization techniques are not scalable."
"We get decent support. It's okay but not great."
"They should build a functional architecture based on queuing."
"Transformation Manager reporting could be better. There are better options for reporting tools these days. We use Microsoft BI sometimes, but Tableau is becoming too expensive. Microsoft BI's visualization features are maturing."
"There is room for improvement in the solution's visualization tool."
 

Pricing and Cost Advice

"Understanding the pricing model for Data Factory is quite complex."
"Data Factory is affordable."
"I don't see a cost; it appears to be included in general support."
"I would rate Data Factory's pricing nine out of ten."
"The price you pay is determined by how much you use it."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"It is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Construction Company
6%
Construction Company
13%
Outsourcing Company
12%
Computer Software Company
10%
Retailer
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
No data available
 

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...
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Also Known As

No data available
Transformation Manager
 

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
Honda, BNP Paribas, RBS, JPMorgan, Volkswagen, Thorn Lighting, OpenSpirit, Rolls-Royce, Ulster Bank
Find out what your peers are saying about Azure Data Factory vs. ETL Solutions Transformation Manager and other solutions. Updated: June 2026.
902,988 professionals have used our research since 2012.