Azure Data Factory vs Dataloader.io comparison

Microsoft and Salesforce are both solutions in the Data Integration category. Microsoft is ranked #4 with an average rating of 8.1, while Salesforce is ranked #48 with an average rating of 7.0. Microsoft holds a 2.3% mindshare in DI, compared to Salesforce’s 0.7% 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 96 Azure Data Factory reviews

12,975 Views
9,083 Comparison Views

92% willing to recommend

Dataloader.io

Read 2 Dataloader.io reviews

1,593 Views
1,258 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: June 2026).

Buyer's Guide

Azure Data Factory vs. Dataloader.io

June 2026

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Helped 900,644 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

4th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (5th)

Dataloader.io

Ranking in Data Integration

48th

Average Rating

7.6

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 8.1% compared to the previous year. The mindshare of Dataloader.io is 0.7%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.3%
Dataloader.io	0.7%
Other	97.0%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

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.

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reviewer2542599

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.

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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

"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."

"The tools are impressively well-integrated, allowing quick development of ETL, big data, data warehousing and machine learning solutions with the flexibility to grow and adapt to changing or enhanced requirements."

"My only advice is that Azure Data Factory, particularly for data ingestion, is a good choice."

"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."

"The solution is okay."

"I am one hundred percent happy with the stability."

"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."

"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."

More Azure Data Factory pros

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

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

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

Cons

"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."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"The deployment should be easier."

"Areas for improvement would be the product's performance and its mapping of data flow."

"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."

"There are limitations when processing more than one GD file."

"There aren't many third-party extensions or plugins available in the solution."

"There's space for improvement in the development process of the data pipelines."

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."

"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 price you pay is determined by how much you use it."

"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 is cheap."

"The solution's pricing is competitive."

"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."

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

"The licensing cost is included in the Synapse."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

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

12%

Computer Software Company

Manufacturing Company

Construction Company

20%

Comms Service Provider

15%

Transportation Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	63

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...

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

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...

See all answers

Comparisons

Snowflake vs Azure Data Factory

Compared 5% of the time

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

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

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SSIS vs Dataloader.io

Compared 10% of the time

TetraScience vs Dataloader.io

Compared 10% of the time

Jitterbit Harmony vs Dataloader.io

Compared 10% of the time

DBamp vs Dataloader.io

Compared 8% of the time

Qlik Talend Cloud vs Dataloader.io

Compared 6% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

June 2026

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Buyer's Guide

Data Integration

June 2026

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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 a cloud-based application designed to simplify data import, export, and integration tasks. It caters to users looking for a straightforward data management tool that supports Salesforce.

Users benefit from Dataloader.io's ability to streamline workflows and automate repetitive data-handling processes. Its advanced capabilities allow businesses to efficiently manage large volumes of data, ensuring accuracy and consistency across Salesforce environments. With intuitive scheduling and user-friendly operations, Dataloader.io is a preferred choice for tech-savvy professionals aiming to enhance productivity.

What are the main features of Dataloader.io?

Cloud-based: Access Dataloader.io from anywhere without installation.
Data Scheduling: Automate data tasks to run at specified intervals.
OAuth Authentication: Securely connect to Salesforce without storing passwords.
Support for Bulk API: Handle large data sets efficiently to optimize processing time.
Export/Import: Move data to and from Salesforce easily.
Intuitive Interface: Simple navigation and operation to decrease the learning curve.

What benefits or ROI should be evaluated in reviews?

Time Efficiency: Reduction in manual data processes, freeing up resources.
Data Accuracy: Maintains consistency across Salesforce applications.
Cost Savings: Decreased overhead by minimizing manual intervention.
Scalability: Easily manages increased data volumes as business needs grow.

In industries like retail, Dataloader.io is valuable for managing large customer databases and inventory data. Financial services benefit from its accuracy in processing transaction data. The straightforward design aids sectors with significant data operations, ensuring efficient data handling and smooth information flow within Salesforce.

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

June 2026

Free Report: Azure Data Factory vs. Dataloader.io

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