Azure Data Factory vs ETL Solutions Transformation Manager comparison

Microsoft and ETL Solutions are both solutions in the Data Integration category. Microsoft is ranked #4 with an average rating of 8.2, while ETL Solutions is ranked #53. Microsoft holds a 2.4% 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 94 Azure Data Factory reviews

12,241 Views
8,446 Comparison Views

92% willing to recommend

ETL Solutions Transformatio...

Read 3 ETL Solutions Transformation Manager reviews

1,938 Views
1,357 Comparison Views

100% willing to recommend

Azure Data Factory

ETL Solutions Transformatio...

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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: April 2026).

Buyer's Guide

Azure Data Factory vs. ETL Solutions Transformation Manager

April 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

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (5th)

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 May 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.4%, down from 8.6% compared to the previous year. The mindshare of ETL Solutions Transformation Manager is 1.0%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.4%
ETL Solutions Transformation Manager	1.0%
Other	96.6%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

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.

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Ravi Kuppusamy

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.

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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

"The trigger scheduling options are decently robust."

"Instead of individual people reviewing these files, we were able to automate the ingestion process, which saved a bunch of time and hours of repeated manual work."

"I like that it's a monolithic data platform. This is why we propose these solutions."

"We have been using drivers to connect to various data sets and consume data."

"From my experience so far, the best feature is the ability to copy data to any environment."

"I like how you can create your own pipeline in your space and reuse those creations."

"It is easy to integrate."

"I can do everything I want with SSIS and Azure Data Factory."

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."

"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."

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

Cons

"Understanding the pricing model for Data Factory is quite complex. It needs to be simplified, and easier to understand."

"The initial setup is not very straightforward."

"They should work on optimizing their licensing model and pricing structure."

"Lacks a decent UI that would give us a view of the kinds of requests that come in."

"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."

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

"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."

"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."

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."

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

"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 is a pay-as-you-go model, where you pay for what you consume."

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

"This is a cost-effective solution."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

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

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

"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."

"The cost is based on the amount of data sets that we are ingesting."

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

12%

Computer Software Company

10%

Manufacturing Company

Government

Construction Company

14%

Computer Software Company

12%

Outsourcing Company

11%

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	63

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...

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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 5% of the time

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Compared 3% of the time

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Compared 3% of the time

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Compared 5% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

May 2026

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Buyer's Guide

Data Integration

May 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

April 2026

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