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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
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
92
Ranking in other categories
Cloud Data Warehouse (2nd)
ETL Solutions Transformatio...
Ranking in Data Integration
37th
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 October 2025, in the Data Integration category, the mindshare of Azure Data Factory is 5.2%, down from 11.0% compared to the previous year. The mindshare of ETL Solutions Transformation Manager is 0.5%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory5.2%
ETL Solutions Transformation Manager0.5%
Other94.3%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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
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

"The scalability of the product is impressive."
"The security of the agent that is installed on-premises is very good."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"We have been using drivers to connect to various data sets and consume data."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"It is among the best, even if not widely known."
"It is a reliable solution."
"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

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."
"We have experienced some issues with the integration. This is an area that needs improvement."
"When we initiated the cluster, it took some time to start the process."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"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."
"They should build a functional architecture based on queuing."
 

Pricing and Cost Advice

"Pricing is comparable, it's somewhere in the middle."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"Data Factory is expensive."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"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."
"The pricing is a bit on the higher end."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"Understanding the pricing model for Data Factory is quite complex."
"It is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
7%
Computer Software Company
22%
Financial Services Firm
13%
Healthcare Company
11%
Retailer
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
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...
What is your experience regarding pricing and costs for ETL Solutions Transformation Manager?
ETL Solutions Transformation Manager is much more affordable than other solutions like AWS, Blue, or Informatica. Even though some competitors may offer seemingly economical pricing, the resource c...
What needs improvement with ETL Solutions Transformation Manager?
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 anal...
 

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: September 2025.
869,760 professionals have used our research since 2012.