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Azure Data Factory vs Dataloader.io 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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (2nd)
Dataloader.io
Ranking in Data Integration
50th
Average Rating
7.6
Reviews Sentiment
7.5
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.8%, down from 9.7% compared to the previous year. The mindshare of Dataloader.io is 0.6%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.8%
Dataloader.io0.6%
Other96.6%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
reviewer2542599 - PeerSpot reviewer
Lead Database Administrator at a insurance company with 201-500 employees
Integrating external keys seamlessly while has transaction constraints
I find DataLoader's ability to easily integrate with external keys valuable, which is a bit more challenging with DBM. It provides automation for scheduling data loads, and we use the server's functionality for this. Additionally, DataLoader is cost-effective since it is free. As long as I have stable network access, uploading and downloading data is straightforward.

Quotes from Members

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

Pros

"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."
"It is a complete ETL Solution."
"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 initial setup is pretty simple and it can be deployed in a couple of hours."
"Its integrability with the rest of the activities on Azure is most valuable."
"Azure Data Factory is a very easy to use tool."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."
"he product’s most valuable feature is ease of access."
"DataLoader is cost-effective since it is free."
"I find DataLoader's ability to easily integrate with external keys valuable, which is a bit more challenging with DBM."
 

Cons

"From my perspective, the pricing seems like it could be more user-friendly."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"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."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components."
"When you raise an issue, sometimes the people who are available are unfamiliar with that particular technology, so they have to route the issue to the concerned person."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"I have not found any real shortcomings within the product."
"The pricing scheme is very complex and difficult to understand."
"DataLoader has limitations, including constraints with file sizes and transactions."
"Dataloader has limitations, including constraints with file sizes and transactions. Additionally, at times it can be slow, and when integrating DBM, we find it more complex than Dataloader."
"We need help with large data migrations. It only works well for a few thousand records or less than a million records."
 

Pricing and Cost Advice

"The solution's pricing is competitive."
"I would rate Data Factory's pricing nine out of ten."
"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."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"The product is inexpensive and economical."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
Large Enterprise57
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 is your experience regarding pricing and costs for Dataloader.io?
Dataloader.io is cost-effective, particularly since it is free.
What needs improvement with Dataloader.io?
DataLoader has limitations, including constraints with file sizes and transactions. Additionally, at times it can be slow, and when integrating DBM, we find it more complex than DataLoader.
What advice do you have for others considering Dataloader.io?
For small to mid-range businesses, DataLoader is perfectly fine, offering everything needed for uploading. On a scale of one to ten, I would rate DataLoader a seven or eight depending on specific n...
 

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
UCSF, Box, CareFusion, Unilever, Hershey's
Find out what your peers are saying about Azure Data Factory vs. Dataloader.io and other solutions. Updated: March 2026.
885,311 professionals have used our research since 2012.