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Azure Data Factory vs Informatica PowerCenter comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 8, 2024
 

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 PowerCenter
Ranking in Data Integration
2nd
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
80
Ranking in other categories
Data Visualization (8th)
 

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.1%, down from 13.3% compared to the previous year. The mindshare of Informatica PowerCenter is 10.9%, up from 10.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Q&A Highlights

PiyushAgarwal - PeerSpot reviewer
Aug 23, 2023
 

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.
Lars Borchers - PeerSpot reviewer
A stable and reliable product that provides a variety of features for data integration
The solution is not for newcomers. It has an old touch. The solution must improve the integration with new services. It was part of the program at Informatica when they moved to their cloud platform. It is integrated. However, from an on-premise perspective, we need to buy licenses for PowerExchange. If we want a native driver to access a special service, we need to extend our license to those services. It is expensive. I don't like that it's not all included in the solution.

Quotes from Members

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

Pros

"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."
"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"The function of the solution is great."
"Allows more data between on-premises and cloud solutions"
"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 most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"Complex transformations can be easily achieved by using PowerCenter. The processing layer does transformations and other things. About 80% of my transformations can be achieved by using the middle layer. For the remaining 15% to 20% transformations, I can go in and create stored procedures in the respective databases. Mapplets is the feature through which we can reuse transformations across pipelines. Transformations and caching are the key features that we have been using frequently. Informatica PowerCenter is one of the best solutions or products in the data integration space. We have extensively used PowerCenter for integration purposes. We usually look at the best bridge solution in our architecture so that it can sustain for maybe a couple of years. Usually, we go with the solution that fits best and has proven and time-tested technology."
"It provides monitoring and we can therefore be aware of what is happening when we are handling jobs."
"Reusable definition of data sources and the out-of-the-box availability of a large number maplets for common transformation functions."
"Good product if you are trying implement data quality, data integration, and data management projects."
"Error handling capability is quite good in Informatica PowerCenter because it provides a very detailed session log, which is really helpful to identify errors."
"It has helped us monetize."
"The most valuable aspects of Informatica PowerCenter are the many features, ease of use, and user-friendliness."
"The most valuable features of Informatica PowerCenter are the ease of use, and development, and is simple to find resources."
 

Cons

"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"The support and the documentation can be improved."
"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."
"It would be better if it had machine learning capabilities."
"In the future, I would like to see Informatica PowerCenter integrate a more powerful dashboard."
"PowerCenter could integrate better with cloud applications. We had to do a lot of configuration work using API integrations to connect with cloud applications. Informatica Cloud Data Integration has a generic connector that you can use directly, so it's much easier."
"I would like to see it be able to import data from NoSQL."
"Its interface can be modernized. It is an old product. I have been working with it for 14 years, and it still looks the same. It hasn't been modernized much. It also needs to handle more modern formats, such as JSON files. It works with the old text files and databases, but it does not always work with the newer, modern stuff. You need to make your own programs to support that kind of stuff. Support is also a kind of difficult with Informatica. They don't do direct support and rely on using their distributors around the globe for support, which means that you kind of have to go through this layer of different companies before you get help."
"They should release new versions for the solution's on-premises setup."
"It should be more cloud-centric than on-prem-centric."
"The real-time database connectivity when getting the real-time data using the VPN is an area that needs improvement."
"This solution needs the functionality to do batch processing of data. It also lacks connectivity to NoSQL, unstructured data sources."
 

Pricing and Cost Advice

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"The cost is based on the amount of data sets that we are ingesting."
"The pricing model is based on usage and is not cheap."
"Pricing is comparable, it's somewhere in the middle."
"The price is fair."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"ADF is cheaper compared to AWS."
"Data Factory is expensive."
"The price of Informatica PowerCenter is expensive, but it does give value."
"I consider this to be an expensive product."
"We have a site license, but we do pay by the division."
"Its licensing is expensive in terms of scaling."
"We are satisfied with the pricing."
"I would rate the pricing for this solution a six out of ten. The exact pricing depends on various products that you have."
"The license model is CPU based."
"Pricing for Informatica PowerCenter isn't cheap, but if I compare it with IBM, it's as expensive as IBM, however, Informatica PowerCenter is more innovative, especially when compared to a giant company such as IBM that has thousands of products. Informatica PowerCenter is limited only to data management, but it has new features that come out every quarter. Points for ease of use and flexibility go to Informatica PowerCenter, but price-wise, IBM and Informatica are equal because they're both expensive."
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Comparison Review

it_user90069 - PeerSpot reviewer
Feb 20, 2014
Informatica PowerCenter vs. Microsoft SSIS - each technology has its advantages but also have similarities
Technology has made it easier for businesses to organize and manipulate data to get a clearer picture of what’s going on with their business. Notably, ETL tools have made managing huge amounts of data significantly easier and faster, boosting many organizations’ business intelligence operations…
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
19%
Computer Software Company
13%
Manufacturing Company
7%
Insurance Company
7%
 

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 is better - SSIS or Informatica PowerCenter?
SSIS PowerPack is a group of drag and drop connectors for Microsoft SQL Server Integration Services, commonly called SSIS. The collection helps organizations boost productivity with code-free compo...
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...
How do you evaluate the pricing model of Informatica PowerCenter?
The pricing model of Informatica PowerCenter is suitable for big companies and enterprises. This is an amazing product, and it certainly does its job, however, if you are a medium or small business...
 

Also Known As

No data available
PowerCenter
 

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
University of Texas MD Anderson Cancer Center, LexisNexis, Rabobank
Find out what your peers are saying about Azure Data Factory vs. Informatica PowerCenter and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.