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Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

 

Comparison Buyer's Guide

Executive Summary

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
6.7
Number of Reviews
96
Ranking in other categories
Data Integration (5th), Cloud Data Warehouse (7th)
Infogix Data360 Analyze [EOL]
Average Rating
7.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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.
reviewer1321299 - PeerSpot reviewer
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.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."
"The solution is okay."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"The overall architecture has been very valuable to us, as it has allowed us to scale up pretty rapidly."
"It is very modular; it works well, is very flexible, and you can easily bring in outside capabilities and build any features you want."
"The most valuable feature of this solution would be ease of use."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"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

"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."
"It would be helpful if they could adjust the data capture feature so that when there are source-side changes ADF could automatically figure it out."
"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."
"I do not have any notes for improvement."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"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

"I would rate Data Factory's pricing nine out of ten."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"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."
"Product is priced at the market standard."
"Pricing is comparable, it's somewhere in the middle."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"ADF is cheaper compared to AWS."
"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%
Manufacturing Company
9%
Computer Software Company
9%
Construction Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
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.
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...
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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Overview

 

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 Informatica, Microsoft, Palantir and others in Data Integration. Updated: July 2026.
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