Azure Data Factory vs Dataloader.io comparison

Why PeerSpot?

Microsoft and Salesforce are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while Salesforce is ranked #51 with an average rating of 7.0. Microsoft holds a 2.2% 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

16,078 Views
11,255 Comparison Views

92% willing to recommend

Dataloader.io

Read 2 Dataloader.io reviews

2,486 Views
1,939 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: November 2026).

Buyer's Guide

Azure Data Factory vs. Dataloader.io

November 2026

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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

6th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (8th)

Dataloader.io

Ranking in Data Integration

51st

Average Rating

7.6

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 4.4% compared to the previous year. The mindshare of Dataloader.io is 0.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.2%
Dataloader.io	0.7%
Other	97.1%

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

"This is an excellent tool for pipeline orchestration; connecting the different components and activities as well as gathering data."

"The most valuable feature of this solution is that it allows more data between on-premises and cloud solutions."

"Its integrability with the rest of the activities on Azure is most valuable."

"The data pipeline and the orchestration functionality are the most valuable aspects of the solution, and the interface is very good, as it seeks to be very responsive and intuitive."

"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS."

"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."

"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"It is beneficial that the solution is written with Spark as the back end."

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

"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."

"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."

"The only challenge with Azure Data Factory is its exception-handling mechanism."

"It can improve from the perspective of active logging. It can provide active logging information."

"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."

"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."

"My only problem is the seamless connectivity with various other databases, for example, SAP."

"It's essentially just a black box. There is some monitoring that can be done, but when something goes wrong, even simple fixes are difficult to troubleshoot."

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

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

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

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"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."

"It's not particularly expensive."

"The solution's pricing is competitive."

"Product is priced at the market standard."

More Azure Data Factory pricing and cost advice

"The product is inexpensive and economical."

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Top Industries

By visitors reading reviews

Manufacturing Company

11%

Financial Services Firm

10%

Outsourcing Company

Computer Software Company

Construction Company

19%

Comms Service Provider

19%

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	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...

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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 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

SSIS vs Dataloader.io

Compared 9% of the time

Jitterbit Harmony vs Dataloader.io

Compared 9% of the time

TetraScience vs Dataloader.io

Compared 8% of the time

DBamp vs Dataloader.io

Compared 8% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Dataloader.io

Compared 4% of the time

More Dataloader.io Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

October 2026

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 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

November 2026

Free Report: Azure Data Factory vs. Dataloader.io

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