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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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
ETL Solutions Transformatio...
Ranking in Data Integration
55th
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 January 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.2%, down from 10.0% compared to the previous year. The mindshare of ETL Solutions Transformation Manager is 0.9%, 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 Factory3.2%
ETL Solutions Transformation Manager0.9%
Other95.9%
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.
Ravi Kuppusamy - PeerSpot reviewer
CEO and Founder at BAssure Solutions
It lets us create models so we can generate real-time predictions and insights for a our clients
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. I would like it if we could set the solution up to process and respond to real-time events. For example, say I want to configure an app to run based on the mileage a car has driven, and I configure the metering system, so the event occurs every 15 days. Let's say we want to automatically send an alert to EMS, police, etc. if a car gets into an accident. Transformation Manager is more of a conventional tool for reporting, extracting volume, bulk loading, etc. but there should be more provisions for dealing with real-time events, creating some insights, and dealing with perishable data. Ten minutes after the accident, the data doesn't have value. It has value before you saved the person.

Quotes from Members

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

Pros

"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"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."
"It is a complete ETL Solution."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"We haven't had any issues connecting it to other products."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"I can do everything I want with SSIS and Azure Data Factory."
"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."
"It is a reliable solution."
 

Cons

"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."
"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."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"The one element of the solution that we have used and could be improved is the user interface."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"The setup and configuration process could be simplified."
"I have not found any real shortcomings within the product."
"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

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"The pricing is a bit on the higher end."
"The price is fair."
"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."
"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."
"The solution is cheap."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"The licensing cost is included in the Synapse."
"It is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
9%
Government
7%
Computer Software Company
16%
Retailer
12%
Outsourcing Company
10%
Performing Arts
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
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: December 2025.
881,114 professionals have used our research since 2012.