Azure Data Factory vs ETL Solutions Transformation Manager comparison

Microsoft and ETL Solutions are both solutions in the Data Integration category. Microsoft is ranked #5 with an average rating of 7.9, while ETL Solutions is ranked #53. Microsoft holds a 2.3% mindshare in DI, compared to ETL Solutions’s 1.0% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of ETL Solutions users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

14,099 Views
9,728 Comparison Views

92% willing to recommend

ETL Solutions Transformatio...

Read 3 ETL Solutions Transformation Manager reviews

2,592 Views
1,866 Comparison Views

100% willing to recommend

Azure Data Factory

ETL Solutions Transformatio...

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

ETL Solutions Transformation Manager and Azure Data Factory compete in the data integration space. Azure Data Factory has the upper hand with its extensive features, while ETL Solutions Transformation Manager offers favorable pricing and support.

Features: ETL Solutions Transformation Manager provides robust transformation capabilities, flexibility in handling complex data scenarios, and personalized customer support. Azure Data Factory includes seamless cloud integration, diverse data source connectivity, and advanced analytics options, offering a comprehensive feature set ideal for cloud-native operations.

Ease of Deployment and Customer Service: ETL Solutions Transformation Manager ensures straightforward deployment with dedicated customer support, making it user-friendly. Azure Data Factory, integrated into the Microsoft Azure ecosystem, streamlines cloud-based deployment but requires more technical expertise. ETL Solutions provides more personalized assistance, beneficial for users seeking direct contact.

Pricing and ROI: ETL Solutions Transformation Manager generally offers a competitive pricing model with a clear ROI, suitable for budget-conscious buyers. Azure Data Factory's pricing reflects its rich feature offering, providing higher long-term ROI within Azure services. The pricing difference highlights the balance between initial budget considerations and investment in extensive capabilities.

To learn more, read our detailed Azure Data Factory vs. ETL Solutions Transformation Manager Report (Updated: August 2026).

Buyer's Guide

Azure Data Factory vs. ETL Solutions Transformation Manager

August 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 Data Integration

5th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

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

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.2% compared to the previous year. The mindshare of ETL Solutions Transformation Manager is 1.0%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.3%
ETL Solutions Transformation Manager	1.0%
Other	96.7%

Data Integration

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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Vijayraj Amin

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.

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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 think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."

"It makes it easy to collect data from different sources."

"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."

"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."

"It is easy to integrate."

"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

"The solution has a good interface and the integration with GitHub is very useful."

More Azure Data Factory pros

"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."

"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."

"It is among the best, even if not widely known."

Cons

"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."

"Azure Data Factory uses many resources and has issues with parallel workflows."

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."

"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."

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

"I did not see any positive impact from Azure Data Factory overall."

"To my mind, the solution needs to be more connectable to its own services."

"The main challenge with implementing Azure Data Factory is that it processes data in batches, not near real-time. To achieve near real-time processing, we need to schedule updates more frequently, which can be an issue. Its interface needs to be lighter."

More Azure Data Factory cons

"We get decent support. It's okay but not great."

"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."

"They should build a functional architecture based on queuing."

"There is room for improvement in the solution's visualization tool."

Pricing and Cost Advice

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"ADF is cheaper compared to AWS."

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

"The licensing cost is included in the Synapse."

More Azure Data Factory pricing and cost advice

"It is an expensive solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Outsourcing Company

13%

Construction Company

13%

Computer Software Company

10%

Performing Arts

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

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.

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...

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Compared 3% of the time

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Compared 3% of the time

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Compared 8% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

August 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

August 2026

ETL Solutions Transformation Manager report

Download ETL Solutions Transformation Manager product report

Also Known As

No data available

Transformation Manager

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

ETL Solutions Transformation Manager efficiently manages data transformations for complex systems, offering scalability and flexibility. It is designed to streamline data processing tasks for businesses with robust data activity needs.

Specializing in data integration, ETL Solutions Transformation Manager enables businesses to manage and transform data with ease. Its exceptional support for diverse data sources, combined with powerful transformation capabilities, caters to the demanding needs of enterprises. The software's ability to handle intricate data processes ensures businesses maintain data accuracy and consistency across platforms.

What features define its capabilities?

Comprehensive Data Integration: Connects to various data sources, promoting seamless data flow.
Powerful Transformation Engine: Transforms complex data sets, facilitating efficient processing and analysis.
Scalability: Grows with the business demands, supporting an increase in data volume and complexity.
Flexibility: Adapts to changing business requirements, enabling customized transformations.

What benefits or ROI should users anticipate?

Cost Efficiency: Reduces time and resources spent on data processing, enhancing operational efficiency.
Improved Data Accuracy: Ensures accurate data handling, minimizing errors and increasing reliability.
Time Savings: Automates repetitive tasks, freeing up time for strategic initiatives.
Enhanced Decision Making: Provides valuable insights through comprehensive data analysis, supporting informed business strategies.

ETL Solutions Transformation Manager finds applications in industries such as finance, healthcare, and e-commerce where data integrity and timely processing are critical. By supporting complex transformation requirements, it allows these industries to maintain operational excellence and competitiveness in their respective markets.

ETL Solutions

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

Buyer's Guide

Azure Data Factory vs. ETL Solutions Transformation Manager

August 2026

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