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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
5th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Cloud Data Warehouse (7th)
DBamp
Ranking in Data Integration
49th
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 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 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 Factory2.3%
DBamp0.4%
Other97.3%
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

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."
"It is easy to deploy workflows and schedule jobs."
"The data copy template is a valuable feature."
"I can do everything I want with SSIS and Azure Data Factory."
"It works very well with Azure Data Factory to pull the records, parse them quickly and post them in the database and data warehouse."
"Azure Data Factory is a very easy to use ETL tool for loading and transforming data from one location to another."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"It is a complete ETL Solution."
"Their support is good, very responsive despite being overseas."
"DBM allows integration with SQL Server, which is beneficial for Microsoft."
 

Cons

"We have experienced some issues with the integration. This is an area that needs improvement."
"Additionally, the ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features."
"The pricing model should be more transparent and available online."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"I would like to see this time travel feature in Snowflake added to Azure Data Factory."
"Azure Data Factory is a bit complicated compared to Informatica. There are a lot of connectors that are missing and there are a lot of instances where I need to create a server and install Integration Runtime."
"DBM is a bit more complicated when compared to DataLoader, especially for more complex operations."
 

Pricing and Cost Advice

"The pricing is a bit on the higher end."
"The price you pay is determined by how much you use it."
"This is a cost-effective solution."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"Data Factory is expensive."
"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."
"Data Factory is affordable."
"The solution's pricing is competitive."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
9%
Construction Company
7%
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
Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: August 2026.
909,679 professionals have used our research since 2012.