Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

Microsoft and Precisely are both solutions in the Data Integration category. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Precisely users who would recommend it.

Azure Data Factory

Read 94 Azure Data Factory reviews

10,752 Views
7,526 Comparison Views

92% willing to recommend

Infogix Data360 Analyze [EOL]

Read 1 Infogix Data360 Analyze [EOL] review

100% willing to recommend

Azure Data Factory

Infogix Data360 Analyze [EOL]

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Executive Summary

We performed a comparison between Azure Data Factory and Infogix Data360 Analyze [EOL] based on real PeerSpot user reviews.

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

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

Buyer's Guide

Data Integration

February 2026

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Helped 884,976 peers since 2012

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

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (3rd), Cloud Data Warehouse (2nd)

Infogix Data360 Analyze [EOL]

Average Rating

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

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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reviewer1321299

Data Analytics Consultant at velocity

Easy drag-and-drop interface and supports custom Python functions, but the performance needs to be better

The memory processing needs to be improved because when you deal with a large amount of data, the interface tends to hang a little bit. When the system boots up, it can take between two and five minutes, depending on the system memory (RAM). If the system is low on memory then it takes a long time to start up. If you are not familiar with Python then this product will be a little more difficult for you. It can take a long time to migrate from one version to the next because there are a lot of processes to deal with.

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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

"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."

"The initial setup is pretty simple and it can be deployed in a couple of hours."

"This is an excellent tool for pipeline orchestration; connecting the different components and activities as well as gathering data."

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

"It is a complete ETL Solution."

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

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."

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

More Azure Data Factory pros

"The drag-and-drop functionality makes it easy for business users."

"This solution allows you to include your own functions that are coded in Python."

Cons

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

"The product could provide more ways to import and export data."

"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."

"There aren't many third-party extensions or plugins available in the solution."

"DataStage is easier to learn than Data Factory because it's more visual."

"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."

"The deployment should be easier."

More Azure Data Factory cons

"The memory processing needs to be improved because when you deal with a large amount of data, the interface tends to hang a little bit."

Pricing and Cost Advice

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

"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."

"The price you pay is determined by how much you use it."

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

"Data Factory is expensive."

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

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

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

More Azure Data Factory pricing and cost advice

"The open-source version is free to use, although it has a limitation of two-million records."

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

11%

Manufacturing Company

Government

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	20
Large Enterprise	57

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 5% of the time

Palantir Foundry vs Azure Data Factory

Compared 4% of the time

FME vs Azure Data Factory

Compared 4% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

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Alteryx Designer vs Infogix Data360 Analyze [EOL]

Compared 65% of the time

More Infogix Data360 Analyze [EOL] Competitors

Product Reports

Buyer's Guide

Azure Data Factory

March 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

February 2026

Download Infogix Data360 Analyze [EOL] product report

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

The most successful businesses have common denominators: maximizing organizational efficiencies, mitigating risk, growing revenue and innovating — fast. Data360 Analyze is the fastest way to aggregate and organize large amounts of data to uncover valuable insights across business units. Easily access, acquire, prepare and analyze quality data with its intuitive browser-based architecture.

Precisely

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

citi, swedbank, RSA, MasterCard, travelers, telstra

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

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