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

17,973 Views
14,229 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: February 2025).

Buyer's Guide

Data Integration

February 2025

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Helped 842,592 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

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

"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"Its integrability with the rest of the activities on Azure is most valuable."

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

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

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

"Data Factory's most valuable feature is Copy Activity."

"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."

More Azure Data Factory pros

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

Cons

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

"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."

"The initial setup is not very straightforward."

"The main challenge with implementing Azure Data Factory is that it processes data in batches, not near real-time. To achieve near real-time processing, we need to schedule updates more frequently, which can be an issue. Its interface needs to be lighter."

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

"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."

"Lacks in-built streaming data processing."

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

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 price is fair."

"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."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"Data Factory is affordable."

"It's not particularly expensive."

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

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

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

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...

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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

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

February 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: February 2025.

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