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Azure Data Factory vs DBamp 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
4th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (5th)
DBamp
Ranking in Data Integration
48th
Average Rating
8.0
Reviews Sentiment
8.7
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.4%, down from 8.6% compared to the previous year. The mindshare of DBamp is 0.4%, 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 Factory2.4%
DBamp0.4%
Other97.2%
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
Integration with existing tools enhances data handling capabilities
DBM allows integration with SQL Server, which is beneficial for Microsoft. While we are only downloading at the moment, we have tested some uploads, and the performance seems better than Data Loader, though it is more complicated. Both products use recommended security protocols, and we don't worry about their security.

Quotes from Members

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

Pros

"Allows more data between on-premises and cloud solutions"
"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"Azure Data Factory is a good tool."
"Azure Data Factory is a low code, no code platform, which is helpful."
"I like the basic features like the data-based pipelines."
"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."
"When it comes to our business requirements, this solution has worked well for us."
"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS"
"Their support is good, very responsive despite being overseas."
"DBM allows integration with SQL Server, which is beneficial for Microsoft."
 

Cons

"Data Factory's monitorability could be better."
"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."
"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"Real-time replication is required, and this is not a simple task."
"The deployment should be easier."
"DBM is a bit more complicated when compared to DataLoader, especially for more complex operations."
"DBM is a bit more complicated when compared to DataLoader, especially for more complex operations."
 

Pricing and Cost Advice

"The licensing is a pay-as-you-go model, where you pay for what you consume."
"Understanding the pricing model for Data Factory is quite complex."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"The solution is cheap."
"I would not say that this product is overly 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."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"I would rate Data Factory's pricing nine out of ten."
Information not available
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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 Enterprise21
Large Enterprise63
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 DBamp?
There is a charge, but it is not a huge charge. It is definitely cost-effective for what is received from it.
What needs improvement with DBamp?
DBM is a bit more complicated when compared to DataLoader, especially for more complex operations. While DataLoader allows mapping, with DBM, everything must be done manually, which increases compl...
What is your primary use case for DBamp?
We are using DBM for uploading. Currently, we are using it to download. However, we want to use it for uploading, however, it is more complicated, so we have not achieved that yet.
 

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
Information Not Available
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