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 93 Azure Data Factory reviews

11,065 Views
7,745 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, IBM and others in Data Integration.

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

Buyer's Guide

Data Integration

January 2026

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Helped 881,384 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

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

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

"The most valuable features are data transformations."

"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."

"It's extremely consistent."

"The data is more scalable."

"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."

"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."

More Azure Data Factory pros

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

Cons

"Data Factory's cost is too high."

"The pricing scheme is very complex and difficult to understand."

"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."

"The initial setup is not very straightforward."

"The one element of the solution that we have used and could be improved is the user interface."

"The solution needs to be more connectable to its own services."

"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."

"I would like to be informed about the changes ahead of time, so we are aware of what's coming."

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."

"This is a cost-effective solution."

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

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

"The solution's pricing is competitive."

"The solution is cheap."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

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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881,384 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

13%

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	19
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...

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 Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 6% of the time

Snowflake vs Azure Data Factory

Compared 6% of the time

FME vs Azure Data Factory

Compared 4% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 4% of the time

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Alteryx Designer vs Infogix Data360 Analyze [EOL]

Compared 100% of the time

More Infogix Data360 Analyze [EOL] Competitors

Product Reports

Buyer's Guide

Azure Data Factory

January 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

January 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, IBM and others in Data Integration. Updated: January 2026.

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