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 86 Azure Data Factory reviews

21,615 Views
17,232 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: December 2024).

Buyer's Guide

Data Integration

December 2024

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Helped 824,067 peers since 2012

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

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.

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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

"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."

"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."

"The most valuable feature is the copy activity."

"The most valuable aspect is the copy capability."

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

"I like the basic features like the data-based pipelines."

"The security of the agent that is installed on-premises is very good."

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

More Azure Data Factory pros

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

Cons

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"I have not found any real shortcomings within the product."

"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."

"The product could provide more ways to import and export data."

"Some known bugs and issues with Azure Data Factory could be rectified."

"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."

"We have experienced some issues with the integration. This is an area that needs improvement."

"The product integration with advanced coding options could cater to users needing more customization."

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

"Product is priced at the market standard."

"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."

"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."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

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

"The solution's pricing is competitive."

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

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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824,067 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Financial Services Firm

32%

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 13% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

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

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

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

December 2024

Download Azure Data Factory product report

Buyer's Guide

Data Integration

December 2024

Download Infogix Data360 Analyze [EOL] product report

Learn More

Microsoft

Precisely

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.

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.

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: December 2024.

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