Azure Data Factory vs Dataloader.io comparison

Microsoft and Salesforce are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.2, while Salesforce is ranked #45 with an average rating of 7.5. Microsoft holds a 8.9% mindshare in DI, compared to Salesforce’s 0.2% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Salesforce users who would recommend it.

Azure Data Factory

Read 90 Azure Data Factory reviews

14,994 Views
12,037 Comparison Views

92% willing to recommend

Dataloader.io

Read 2 Dataloader.io reviews

136 Views
118 Comparison Views

100% willing to recommend

Azure Data Factory

Dataloader.io

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and Dataloader.io based on real PeerSpot user reviews.

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Azure Data Factory vs. Dataloader.io Report (Updated: April 2025).

Buyer's Guide

Azure Data Factory vs. Dataloader.io

April 2025

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Helped 850,236 peers since 2012

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

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

Dataloader.io

Ranking in Data Integration

45th

Average Rating

7.6

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the Data Integration category, the mindshare of Azure Data Factory is 8.9%, down from 12.5% compared to the previous year. The mindshare of Dataloader.io is 0.2%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

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.

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Aditi Bhardwaj

Senior Data Scientist at Peristent Systems

Provides an ease of access and an automated mapping feature

We need help with large data migrations. It only works well for a few thousand records or less than a million records. Above that, we need to look for alternative solutions. They could provide automated transformation or mapping features around 10 to 15 independent data objects. We could have a default mark or limit of free usage for standard objects. It will be helpful. Additionally, we can have more integrations with large data volumes as we need a lot of exercises to handle the files in case of complex sites.

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Quotes from Members

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

Pros

"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."

"Data Factory's most valuable feature is Copy Activity."

"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."

"We use the solution to move data from on-premises to the cloud."

"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."

"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."

"The data copy template is a valuable feature."

"Azure Data Factory is a low code, no code platform, which is helpful."

More Azure Data Factory pros

"I find DataLoader's ability to easily integrate with external keys valuable, which is a bit more challenging with DBM."

"he product’s most valuable feature is ease of access."

"DataLoader is cost-effective since it is free."

Cons

"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."

"When we initiated the cluster, it took some time to start the process."

"Some prebuilt data source or data connection aspects are generic."

"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."

"Azure Data Factory can improve by having support in the drivers for change data capture."

"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."

"The product integration with advanced coding options could cater to users needing more customization."

More Azure Data Factory cons

"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."

"DataLoader has limitations, including constraints with file sizes and transactions."

"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

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

"The pricing is a bit on the higher end."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"This is a cost-effective solution."

"Data Factory is expensive."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

More Azure Data Factory pricing and cost advice

"The product is inexpensive and economical."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

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.

See all answers

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...

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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...

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What do you like most about Dataloader.io?

he product’s most valuable feature is ease of access.

See all answers

What is your experience regarding pricing and costs for Dataloader.io?

Dataloader.io is cost-effective, particularly since it is free.

See all answers

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.

See all answers

Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 11% of the time

Snowflake vs Azure Data Factory

Compared 9% of the time

Alteryx Designer vs Azure Data Factory

Compared 6% of the time

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

Compared 6% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 5% of the time

More Azure Data Factory Competitors

Talend Data Management Platform vs Dataloader.io

Compared 100% of the time

More Dataloader.io Competitors

Product Reports

Buyer's Guide

Azure Data Factory

May 2025

Download Azure Data Factory product report

Buyer's Guide

Data Integration

May 2025

Download Dataloader.io product report

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

Dataloader.io is the data loader for Salesforce. Use the most popular data loader for Salesforce to quickly and securely import, export and delete unlimited amounts of data for your enterprise. Get started quickly with our simple, 100% cloud solution.

Salesforce

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

Buyer's Guide

Azure Data Factory vs. Dataloader.io

April 2025

Free Report: Azure Data Factory vs. Dataloader.io

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