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Azure Data Factory vs Talend Open Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 20, 2025

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)
Talend Open Studio
Ranking in Data Integration
5th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
50
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 Talend Open Studio is 4.4%, down from 5.1% 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.
Costin Marzea - PeerSpot reviewer
Allows you to develop your own components and can be used as an OEM
Sometimes, scalability is part of planning. It depends on what you mean by scalability. People talk a lot about it, but scalability is not always about system functionality. Sometimes, it may be planning the job you're doing. If you want to split it into several jobs or servers, you don't actually have to have it built in as a functionality. You can create a job using a loop, which runs and controls several jobs in a loop that may be controlled. Scaling should not always be part of the infrastructure based on whether the engine can scale or not. I think it's your plan or project that should scale and split, and you can define these parameters. These parameters include how many servers you want to run or how many executions you want to do on different parts of the data. It's not always an issue of the engine running. Sometimes, your database should be configured to support partitioning. The product may scale very well without partitioning, but if the basic response is very slow, you didn't solve the problem. You should solve the problems at a higher level, not just at the execution level. They should be solved at the database level and communication level, and you should have firewalls. We are trying to add to the open source the ability to generate code for containers and Kubernetes that exist in the subscription version. Once you do this, Kubernetes will take care of the scaling, so there is no problem.

Quotes from Members

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

Pros

"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"The data is more scalable."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"The most valuable feature of this solution would be ease of use."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"It is user-friendly and the interface is good."
"The most interesting aspect of the solution for us is that Talend Open Studio has a good balance between the features and the cost of the data management platform."
"This product is very easy to use."
"It is easy to use and covers most of the functions needed. We can use the code without any extra effort. The open source is very good. They have the same commercials with additional connectors. The graphical design environment is also very easy."
"Talend Open Studio is easy to create jobs. We use the basic functionality and it is very good."
"The initial setup of the product was very easy."
"The main differentiator that I have seen between Talend and other data integration tools is the ability to view the data pipeline in the form of a program."
"The most valuable feature for me when it comes to this solution is that it's easy to use."
 

Cons

"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"There's space for improvement in the development process of the data pipelines."
"I have not found any real shortcomings within the product."
"There are limitations when processing more than one GD file."
"The Microsoft documentation is too complicated."
"It is complicated to understand the configuration process for email components."
"Having additional training materials, such as a video tutorial, would be an improvement."
"Technical support and customer service need to be improved."
"As for improvement or additional features, I would like to know how to use Java in Talend and also how to use Talend in the cloud or in big data. I would prefer to have storage directly on Talend."
"Talend Open Studio has a lot of capabilities, but there is some restriction. For example, if we want to connect to an SAP system, Open Studio cannot do it. We need to go with an enterprise version. Additionally, the monitoring features could improve."
"The user interface could be made simpler."
"The stability of the solution could improve when running jobs. There can be errors when running projects but in the end, it works well and the errors do not impact the result."
"It needs better installation configuration for other databases. Although the installation allows you to select another database, this doesn't mean that all connection points in the application point to the database selected. You actually need to do a search through the entire install to locate the configuration settings and change them."
 

Pricing and Cost Advice

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"This is a cost-effective solution."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"ADF is cheaper compared to AWS."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"The price is fair."
"The pricing model is based on usage and is not cheap."
"The cost, particularly in Africa, is quite high."
"The solution will be more expensive if you have a low data volume and a large number of developers."
"Pricing and licensing are fairly straightforward. It is reasonably priced and managed."
"I am using the open-source version and it is free."
"Pricing is always a challenge. It is quite an expensive model, but because the platform is so simple to use, we haven't had to purchase any additional licenses."
"It is an open-source product."
"There are many versions available and one is open-sourced which is free."
"Talend Open Studio is priced too high."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
Financial Services Firm
17%
Computer Software Company
13%
Manufacturing Company
8%
Government
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...
How does Talend Open Studio compare with AWS Glue?
We reviewed AWS Glue before choosing Talend Open Studio. AWS Glue is the managed ETL (extract, transform, and load) from Amazon Web Services. AWS Glue enables AWS users to create and manage jobs in...
What do you like most about Talend Open Studio?
It is easy to use and covers most of the functions needed. We can use the code without any extra effort. The open source is very good. They have the same commercials with additional connectors. The...
 

Also Known As

No data available
Open Studio
 

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
Almerys, BF&M, Findus
Find out what your peers are saying about Azure Data Factory vs. Talend Open Studio and other solutions. Updated: July 2025.
861,524 professionals have used our research since 2012.