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Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

 

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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
7.0
Number of Reviews
91
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
Infogix Data360 Analyze [EOL]
Average Rating
7.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
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.
reviewer1321299 - PeerSpot reviewer
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

"The data copy template is a valuable feature."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"The flexibility that Azure Data Factory offers is great."
"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."
"The most valuable feature of this solution would be ease of use."
"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."
"It is a complete ETL Solution."
"It is beneficial that the solution is written with Spark as the back end."
"The drag-and-drop functionality makes it easy for business users."
 

Cons

"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"Real-time replication is required, and this is not a simple task."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"Data Factory's cost is too high."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"We require Azure Data Factory to be able to connect to Google Analytics."
"The speed and performance need to be improved."
"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 don't see a cost; it appears to be included in general support."
"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."
"It's not particularly expensive."
"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."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"This is a cost-effective solution."
"Data Factory is affordable."
"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
9%
Healthcare Company
6%
No data available
 

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.
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
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