Azure Data Factory vs Dataloader.io comparison

Microsoft and Salesforce are both solutions in the Data Integration category. Microsoft is ranked #5 with an average rating of 7.9, while Salesforce is ranked #50 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 97 Azure Data Factory reviews

14,099 Views
9,728 Comparison Views

92% willing to recommend

Dataloader.io

Read 2 Dataloader.io reviews

1,866 Views
1,474 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: August 2026).

Buyer's Guide

Azure Data Factory vs. Dataloader.io

August 2026

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Helped 909,725 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

5th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th)

Dataloader.io

Ranking in Data Integration

50th

Average Rating

7.6

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.2% 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

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

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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

"It works very well with Azure Data Factory to pull the records, parse them quickly and post them in the database and data warehouse."

"We haven't had any issues connecting it to other products."

"The features that I've found most valuable, in order: That it is a complete ETL Solution, the second one is interface, the third one workflow, and the fourth one ease of use."

"The scalability of the product is impressive."

"The reason that we implemented this product is for the full integration with the whole Azure environment."

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"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."

More Azure Data Factory pros

"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

"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."

"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."

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"I would like to see this time travel feature in Snowflake added to Azure Data Factory."

"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."

"If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features."

"I do not have any notes for improvement."

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

More Azure Data Factory cons

"We need help with large data migrations. It only works well for a few thousand records or less than a million records."

"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."

Pricing and Cost Advice

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

"I would rate Data Factory's pricing nine out of ten."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

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

"The licensing cost is included in the Synapse."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"The solution's pricing is competitive."

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

11%

Manufacturing Company

Computer Software Company

Construction Company

20%

Comms Service Provider

18%

Insurance Company

Transportation Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

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 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

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

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Jitterbit Harmony vs Dataloader.io

Compared 11% of the time

TetraScience vs Dataloader.io

Compared 10% of the time

SSIS vs Dataloader.io

Compared 10% of the time

DBamp vs Dataloader.io

Compared 9% 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

August 2026

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Buyer's Guide

Data Integration

August 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

August 2026

Free Report: Azure Data Factory vs. Dataloader.io

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