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

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
86
Ranking in other categories
Cloud Data Warehouse (3rd)
Informatica Intelligent Dat...
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
181
Ranking in other categories
Data Quality (1st), Business Process Management (BPM) (7th), Business-to-Business Middleware (3rd), API Management (7th), Cloud Data Integration (3rd), Data Governance (2nd), Test Data Management (3rd), Cloud Master Data Management (MDM) Solutions (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Metadata Management (1st), Test Data Management Services (4th), Product Information Management (PIM) (1st), Data Observability (2nd)
 

Featured Reviews

Thulani David Mngadi - PeerSpot reviewer
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.
Raj Sethupathi - PeerSpot reviewer
Offers profiling and address standardization but can be complicated
Informatica Data Quality has its data warehouse, primarily using Oracle and some SQL databases. You need a database to host the data. The cleansed version of the data is stored in the data warehouse. It integrates with PowerCenter and other Informatica tools. The integration details can be complex, but a regional setup is involved in this process. Profiling smaller datasets, such as 10,000-50,000 records, worked fine. However, unexpected issues could arise with larger datasets, such as thousands of records or more, especially with tables containing many columns. Handling tables with fifty or more columns can be challenging, even in Excel. A mismatch in data types could cause the entire system to crash. Continual enhancements are being made to address these issues, which can be unique to specific industries like finance and healthcare.

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 of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"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 solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."
"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"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."
"The most important feature is that it can help you do the multi-threading concepts."
"I can do everything I want with SSIS and Azure Data Factory."
"The solution is stable."
"The ability to clean out data and improve the data quality is the best feature."
"The Mapping Designer allows for declarative ETL development (visual scripting) that leverages a wide array of different transformations."
"Performance and flexibility-wise, they're very user-friendly."
"The interface has a great look and feel, and the functionality is so easy."
"The staging and hierarchical features are the most valuable."
"The tool's most valuable feature is bulk upload. We upload files in CSV or Excel format."
"The solution provides increased efficiency while still being user-friendly and easy to operate."
 

Cons

"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"Data Factory's performance during heavy data processing isn't great."
"We require Azure Data Factory to be able to connect to Google Analytics."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"Some known bugs and issues with Azure Data Factory could be rectified."
"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."
"Lacks in-built streaming data processing."
"When the record fails, it's tough to identify and log."
"Inserting the GenAI into the master data management will reduce the overall effort of operational activities."
"Certain applications are not being synced with the ION."
"User/group administration could use improvement."
"Informatica Axon needs more integration connectors so that it can connect to systems and different kinds of datasets."
"With the solution, we had some issues, and we have every day, and we used to open a ticket. Sometimes, there are data issues and transformation issues."
"I think everything related to the APIs and the manageability of the APIs in Informatica MDM are areas where improvements are required."
"Although we are very satisfied with the design of the UI, executing tasks with it can be difficult."
"Once the data is masked, we won't be able to reverse it back to its original value."
 

Pricing and Cost Advice

"The solution's pricing is competitive."
"Pricing appears to be reasonable in my opinion."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"The price is fair."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"Data Factory is expensive."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"The price is comparable."
"Informatica MDM's pricetag should come down. They have to cut some costs."
"Licensing is difficult to understand, but the team is always available to explain anything. They are very helpful."
"I rate the product's pricing a seven on a scale of one to ten, where one is the lowest price and ten is the highest price."
"Its pricing model can be improved."
"Informatica MDM is a costly solution because it comes as a bundle. They are also globally positioning themselves and are definitely working on very upgraded technologies. If someone wanted to do it on the cloud, they have a lot of flexibility because they upgrade themselves according to the current needs. It definitely comes with a lot of features and that's the reason why it's costly. The licensing cost should be approximately one million dollars. It's about four to five times that of other vendors."
"The pricing is quite flexible."
"I have heard from customers that the product comes with a huge license cost."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
17%
Computer Software Company
13%
Manufacturing Company
10%
Insurance Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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...
Which Informatica product would you choose - PowerCenter or Cloud Data Integration?
Complex transformations can easily be achieved using PowerCenter, which has all the features and tools to establish a real data governance strategy. Additionally, PowerCenter is able to manage huge...
What are the biggest benefits of using Informatica Cloud Data Integration?
When it comes to cloud data integration, this solution can provide you with multiple benefits, including: Overhead reduction by integrating data on any cloud in various ways Effective integration ...
Is the support provided by Informatica Cloud Data Integration helpful?
The support that Informatica Cloud Data Integration offers is very helpful. We had some issues with the setup of the product, as our team was not experienced with cloud data integration tools. We ...
 

Also Known As

No data available
ActiveVOS, Active Endpoints, BPM, Address Verification, Persistent Data Masking, Cloud Test Data Management, PIM, , Enterprise Data Catalog, Data Integration Hub, Cloud Data Integration, Data Quality, Cloud API and App Integration
 

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
The Travel Company, Carbonite
Find out what your peers are saying about Azure Data Factory vs. Informatica Intelligent Data Management Cloud (IDMC) and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.