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Azure Data Factory vs Informatica Enterprise Data Lake 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
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Cloud Data Warehouse (2nd)
Informatica Enterprise Data...
Ranking in Data Integration
40th
Average Rating
7.0
Reviews Sentiment
5.9
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2025, in the Data Integration category, the mindshare of Azure Data Factory is 7.9%, down from 12.2% compared to the previous year. The mindshare of Informatica Enterprise Data Lake is 0.2%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

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.
reviewer2330691 - PeerSpot reviewer
A scalable tool that needs a lot of maintenance due to its unstable nature
Governance, data dictionary, and data cataloging are not available in Informatica Enterprise Data Lake. A lot of businesses are facing issues related to understanding the area revolving around insights of data. At Informatica Enterprise Data Lake's level, in our company, we have a lot of redundant data in a lot of our core systems. The basic thing that our company wants is for the product to develop a reporting layer and access data from the document layer so that we can avoid duplication in projects, databases, and data. There is a lot of maintenance to be done owing to the instability users may face every time because of the huge processing capacity as the company has around more than 50 nodes, which causes a lot of maintenance issues because of which a lot of people don't benefit from the platform as it functions in a slow manner. Informatica Enterprise Data Lake's setup process was complex since it doesn't support a lot of real-time systems. Every time, we have to find different tools we can use in our company with the solution since it doesn't support many real-time systems. Even if our company invests in some tools, Informatica Enterprise Data Lake creates too many small files with some issues, which we cannot read because we invested in HBase and Kudu, but performance-wise, the process is slow.

Quotes from Members

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

Pros

"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"Azure Data Factory is a low code, no code platform, which is helpful."
"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 valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"It is easy to integrate."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"We have been using drivers to connect to various data sets and consume data."
"The most valuable aspect is the copy capability."
"The process of using the tool's scalability option is well documented."
 

Cons

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"Some prebuilt data source or data connection aspects are generic."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"When we initiated the cluster, it took some time to start the process."
"Informatica Enterprise Data Lake's setup process was complex since it doesn't support a lot of real-time systems."
 

Pricing and Cost Advice

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"The pricing is a bit on the higher end."
"I don't see a cost; it appears to be included in general support."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"The cost is based on the amount of data sets that we are ingesting."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"Pricing is comparable, it's somewhere in the middle."
"The licenses attached to the solution are highly priced."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
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...
What do you like most about Informatica Enterprise Data Lake?
The process of using the tool's scalability option is well documented.
What is your experience regarding pricing and costs for Informatica Enterprise Data Lake?
The licenses attached to the solution are highly priced. Informatica has licensing models for every product and for every feature, like the web service feature, which is something my company doesn'...
What needs improvement with Informatica Enterprise Data Lake?
Governance, data dictionary, and data cataloging are not available in Informatica Enterprise Data Lake. A lot of businesses are facing issues related to understanding the area revolving around insi...
 

Also Known As

No data available
Informatica Intelligent Data Lake, Intelligent Data Lake
 

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
Information Not Available
Find out what your peers are saying about Microsoft, Informatica, Talend and others in Data Integration. Updated: June 2025.
861,390 professionals have used our research since 2012.