Azure Data Factory vs Infogix Data360 Analyze [EOL] comparison

Azure Data Factory
Read 81 Azure Data Factory reviews
  • 24,893 Views
  • 19,539 Comparison Views
91% willing to recommend
 

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, Oracle and others in Data Integration.

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Data Integration
May 2024
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Helped 787,779 peers since 2012
 

Categories and Ranking

Azure Data Factory
Average Rating
8.0
Number of Reviews
81
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (3rd)
Infogix Data360 Analyze [EOL]
Average Rating
7.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2024, in the Data Integration category, the mindshare of Azure Data Factory is 9.6%, down from 13.6% compared to the previous year. The mindshare of Infogix Data360 Analyze [EOL] is 0.1%, down from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
Unique Categories:
Cloud Data Warehouse
13.6%
 

Featured Reviews

Arpita-Mishra - PeerSpot reviewer
Jan 12, 2023
Faster than other solutions, has multiple connectors, and is easy to set up
I use Azure Data Factory for architecture creation, for example, loading data from Oracle DB to Azure Synapse Analytics, creating facts and dimensions using Azure Data Pipeline, and creating Azure Synapse notebooks for data transformation.  Another use case for Azure Data Factory is dashboard…
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RB
Apr 14, 2020
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

"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"The solution has a good interface and the integration with GitHub is very useful."
"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."
"I like that it's a monolithic data platform. This is why we propose these solutions."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
More Azure Data Factory pros
"The drag-and-drop functionality makes it easy for business users."
 

Cons

"The thing we missed most was data update, but this is now available as of two weeks ago."
"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."
"It would be better if it had machine learning capabilities."
"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 a decent UI that would give us a view of the kinds of requests that come in."
"The deployment should be easier."
"The support and the documentation can be improved."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
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

"ADF is cheaper compared to AWS."
"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."
"I would not say that this product is overly expensive."
"Pricing appears to be reasonable in my opinion."
"Product is priced at the market standard."
"The pricing model is based on usage and is not cheap."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"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
Computer Software Company
13%
Financial Services Firm
13%
Manufacturing Company
8%
Healthcare Company
7%
Financial Services Firm
26%
Healthcare Company
13%
Insurance Company
10%
Comms Service Provider
8%
 

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...
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 PowerCenter vs Azure Data Factory Logo
Informatica PowerCenter vs Azure Data Factory
Compared 13% of the time
Informatica Cloud Data Integration vs Azure Data Factory Logo
Informatica Cloud Data Integration vs Azure Data Factory
Compared 9% of the time
Snowflake vs Azure Data Factory Logo
Snowflake vs Azure Data Factory
Compared 8% of the time
Alteryx Designer vs Azure Data Factory Logo
Alteryx Designer vs Azure Data Factory
Compared 8% of the time
IBM InfoSphere DataStage vs Azure Data Factory Logo
IBM InfoSphere DataStage vs Azure Data Factory
Compared 4% of the time
More Azure Data Factory Competitors
Alteryx Designer vs Infogix Data360 Analyze [EOL] Logo
Alteryx Designer vs Infogix Data360 Analyze [EOL]
Compared 49% of the time
Informatica PowerCenter vs Infogix Data360 Analyze [EOL] Logo
Informatica PowerCenter vs Infogix Data360 Analyze [EOL]
Compared 28% of the time
More Infogix Data360 Analyze [EOL] Competitors
 

Product Reports

Buyer's Guide
Azure Data Factory
June 2024
Azure Data Factory reportDownload Azure Data Factory product report
Buyer's Guide
Data Integration
May 2024
Infogix Data360 Analyze [EOL] reportDownload 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
Buyer's Guide
Data Integration
May 2024
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