Azure Data Factory vs ibi DataMigrator comparison

Why PeerSpot?

Microsoft and Information Builders are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while Information Builders is ranked #36 with an average rating of 9.0. Microsoft holds a 2.2% mindshare in DI, compared to Information Builders’s 0.6% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Information Builders users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

16,078 Views
11,255 Comparison Views

92% willing to recommend

ibi DataMigrator

Read 1 ibi DataMigrator review

2,478 Views
2,057 Comparison Views

100% willing to recommend

Azure Data Factory

ibi DataMigrator

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and ibi DataMigrator based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: October 2026).

Buyer's Guide

Data Integration

October 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 (8th)

ibi DataMigrator

Ranking in Data Integration

36th

Average Rating

9.0

Reviews Sentiment

1.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 4.4% compared to the previous year. The mindshare of ibi DataMigrator is 0.6%, down from 0.6% 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%
ibi DataMigrator	0.6%
Other	97.2%

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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David_Hall

Data Warehouse Analyst at a insurance company with 1,001-5,000 employees

Have seen support quality decline while still relying on long-standing data transformation features

I would assess the tool's error handling and logging features as part of it involves having a sampling thing. Depending on the definition of who's doing this, I used to work at a university where we looked at students who registered, and there were people who could register without specifying their gender. Most people know their gender. Some people would not put their birth date, so their date of birth was the default century. In 1989, we had hundreds of 89-year-olds because it was noted as 1900. What we would do is quickly assess that this is not reasonable; in a college setting, how many 89-year-olds are standing in line for freshman orientation? We could produce transformations on the fly. You can look at stuff, but ultimately, you need to go back to the data. There's logic involved; do you have to have a six-digit zip? Do you need the six plus four? It all depends on your criteria. It's doable, but it takes time, and if there's a lot of that, they usually hire people just to handle it. It's a tool that has its limitations; they haven't added wonderful features, and it's a GUI tool based on a desktop that you can run. Their manuals are pretty good, but we're not really using it actively, so I can't tell you everything right now.

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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

"Azure Data Factory is a low code, no code platform, which is helpful."

"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."

"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."

"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."

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

"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."

"The most valuable feature is the ease in which you can create an ETL pipeline."

"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."

More Azure Data Factory pros

"IBI has led the way for many years because they can read and write any data set."

Cons

"When we initiated the cluster, it took some time to start the process."

"Azure Data Factory's pricing in terms of utilization could be improved."

"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."

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

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"If the user interface was more user friendly and there was better error feedback, it would be helpful."

"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."

"As far as customer service and support with Azure Data Factory, we are not always satisfied with the response time."

More Azure Data Factory cons

"Their products work wonderfully during demos, but when we install them, they don't, and I end up following their manual only to find they forgot to mention something important."

Pricing and Cost Advice

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

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"I would rate Data Factory's pricing nine out of ten."

"The pricing is a bit on the higher end."

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

"The price is fair."

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

"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."

More Azure Data Factory pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Manufacturing Company

10%

Financial Services Firm

10%

Outsourcing Company

Construction Company

18%

Comms Service Provider

15%

Retailer

10%

Transportation 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...

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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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What is your experience regarding pricing and costs for ibi DataMigrator?

I don't have details about the pricing or licensing of ibi DataMigrator. I stay away from money matters; the last time I bought something was 35 years ago while trying to convince people it was wor...

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What needs improvement with ibi DataMigrator?

See all answers

What is your primary use case for ibi DataMigrator?

That's just it with the main use case for us more recently. We have it, we're licensed for it. We can make sure it works, but we don't really use ibi DataMigrator. ibi DataMigrator is an Extract, T...

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Comparisons

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

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

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Informatica PowerCenter vs ibi DataMigrator

Compared 14% of the time

SSIS vs ibi DataMigrator

Compared 14% of the time

ibi Open Data Hub for Mainframe vs ibi DataMigrator

Compared 8% of the time

IBM InfoSphere DataStage vs ibi DataMigrator

Compared 6% of the time

More ibi DataMigrator Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

October 2026

Download ibi DataMigrator product report

Also Known As

No data available

iWay DataMigrator, Information Builders DataMigrator

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

ibi DataMigrator offers a flexible and robust data integration and migration platform designed for seamless data transfer and transformation between systems. Its advanced functionalities support the automation of complex workflows and ensure reliable, efficient data management.

Built to cater to the demanding data workflows of modern enterprises, ibi DataMigrator simplifies data extraction, transformation, and load processes. This platform's strength lies in its ability to integrate diverse data sources, harmonizing data across environments effortlessly. Users benefit from its powerful automation capabilities, reducing the likelihood of errors while improving operational efficiency. Both IT professionals and data engineers find value in its comprehensive suite of tools aimed at streamlining data operations.

What are the key features of ibi DataMigrator?

Automated Scheduling: Schedule tasks to run at optimal times without manual intervention.
Data Transformation: Apply complex transformations to raw data, tailoring it for specific purposes.
Scalability: Handle data migration and transformation for large datasets with ease.
Source Connectivity: Connect effortlessly with a myriad of data sources, supporting diverse environments.

What benefits or ROI should users seek in reviews?

Improved Efficiency: Streamline operations and reduce the time taken for data workflows.
Reduced Errors: Automation minimizes manual errors, enhancing data reliability.
Operational Cost Saving: Lower manual labor and infrastructure costs by optimizing data processes.
Enhanced Decision Making: Access to harmonized data leads to better business insights.

ibi DataMigrator is widely implemented in sectors such as finance, healthcare, and retail. It addresses industry-specific challenges by providing scalable, automated data processing solutions that enhance data accessibility and integrity. Companies benefit from improved compliance and reporting through efficient data management.

Information Builders

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

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Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: October 2026.

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