Azure Data Factory vs ETL Solutions Transformation Manager comparison

Why PeerSpot?

Microsoft and ETL Solutions are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while ETL Solutions is ranked #54. Microsoft holds a 2.2% 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

15,321 Views
10,725 Comparison Views

92% willing to recommend

ETL Solutions Transformatio...

Read 3 ETL Solutions Transformation Manager reviews

3,137 Views
2,290 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: September 2026).

Buyer's Guide

Azure Data Factory vs. ETL Solutions Transformation Manager

September 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

6th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (6th)

ETL Solutions Transformatio...

Ranking in Data Integration

54th

Average Rating

9.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 5.1% compared to the previous year. The mindshare of ETL Solutions Transformation Manager is 1.0%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.2%
ETL Solutions Transformation Manager	1.0%
Other	96.8%

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

"So far, I'm quite happy with the solution overall."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

"Azure Data Factory became more user-friendly when data-flows were introduced."

"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."

"Azure Data Factory is a very easy to use tool."

"Data Factory lets us consolidate those steps into a single pipeline."

"An excellent tool for pipeline orchestration."

"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."

More Azure Data Factory pros

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

"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."

Cons

"There are limitations when processing more than one GD file."

"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."

"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."

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

"Azure Data Factory is a bit complicated compared to Informatica. There are a lot of connectors that are missing and there are a lot of instances where I need to create a server and install Integration Runtime."

"From my perspective, the pricing seems like it could be more user-friendly."

"Some prebuilt data source or data connection aspects are generic."

"The speed and performance need to be improved."

More Azure Data Factory cons

"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."

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

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

Pricing and Cost Advice

"Product is priced at the market standard."

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

"The solution's pricing is competitive."

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

"Understanding the pricing model for Data Factory is quite complex."

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

"The licensing cost is included in the Synapse."

"Pricing is comparable, it's somewhere in the middle."

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

12%

Construction Company

12%

Comms Service Provider

11%

Computer Software Company

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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Comparisons

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Compared 4% of the time

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Compared 3% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

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Compared 8% of the time

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Compared 6% of the time

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Compared 5% of the time

Chain-Sys appCONNECT vs ETL Solutions Transformation Manager

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Product Reports

Buyer's Guide

Azure Data Factory

October 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

September 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

September 2026

Free Report: Azure Data Factory vs. ETL Solutions Transformation Manager

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