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 90 Azure Data Factory reviews

16,157 Views
12,990 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]

Comparison Buyer's Guide

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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, Talend and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: March 2025).

Buyer's Guide

Data Integration

March 2025

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Helped 844,944 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

6.9

Number of Reviews

Ranking in other categories

Data Integration (1st), Cloud Data Warehouse (3rd)

Infogix Data360 Analyze [EOL]

Average Rating

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

Facilitates seamless data pipeline creation with good analytics and and thorough monitoring

Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.

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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

"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."

"The trigger scheduling options are decently robust."

"The data flows were beneficial, allowing us to perform multiple transformations."

"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."

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

"It is a complete ETL Solution."

More Azure Data Factory pros

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

Cons

"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."

"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."

"There's space for improvement in the development process of the data pipelines."

"I do not have any notes for improvement."

"Data Factory's performance during heavy data processing isn't great."

"We require Azure Data Factory to be able to connect to Google Analytics."

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

"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."

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

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

"Data Factory is expensive."

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

"The solution's pricing is competitive."

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

"It's not particularly expensive."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"The solution is cheap."

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

14%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Financial Services Firm

40%

Healthcare Company

16%

Insurance Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

Informatica PowerCenter vs Azure Data Factory

Compared 12% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

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

Compared 7% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 5% of the time

More Azure Data Factory Competitors

No data available

Product Reports

Buyer's Guide

Azure Data Factory

March 2025

Download Azure Data Factory product report

Buyer's Guide

Data Integration

March 2025

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, Talend and others in Data Integration. Updated: March 2025.

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We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.