Azure Data Factory vs DBamp comparison

Microsoft and CData Software are both solutions in the Data Integration category. Microsoft is ranked #4 with an average rating of 8.1, while CData Software is ranked #47 with an average rating of 8.0. Microsoft holds a 2.3% mindshare in DI, compared to CData Software’s 0.4% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of CData Software 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

DBamp

Read 1 DBamp review

854 Views
794 Comparison Views

100% willing to recommend

Azure Data Factory

DBamp

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and DBamp based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: June 2026).

Buyer's Guide

Data Integration

June 2026

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Helped 902,588 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)

DBamp

Ranking in Data Integration

47th

Average Rating

8.0

Reviews Sentiment

8.7

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 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
Product	Mindshare (%)
Azure Data Factory	2.3%
DBamp	0.4%
Other	97.3%

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

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.

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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

"We use the solution to move data from on-premises to the cloud."

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

"Azure Data Factory is great because it's a cloud service; you do not have to take care of the installation and configuration yourself."

"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."

"The most valuable feature is the ease in which you can create an ETL pipeline."

"The most valuable aspect is the copy capability."

"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."

"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."

More Azure Data Factory pros

"Their support is good, very responsive despite being overseas."

"DBM allows integration with SQL Server, which is beneficial for Microsoft."

Cons

"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."

"Azure Data Factory can improve by having support in the drivers for change data capture."

"In the next release, it's important that some sort of scheduler for running tasks is added."

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

"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."

"Data Factory's performance during heavy data processing isn't great."

"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."

"If the user interface was more user friendly and there was better error feedback, it would be helpful."

More Azure Data Factory cons

"DBM is a bit more complicated when compared to DataLoader, especially for more complex operations."

Pricing and Cost Advice

"Pricing is comparable, it's somewhere in the middle."

"I don't see a cost; it appears to be included in general support."

"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."

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

"ADF is cheaper compared to AWS."

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

"The solution is cheap."

"The solution's pricing is competitive."

More Azure Data Factory pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

Manufacturing Company

Construction Company

No data available

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...

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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.

See all answers

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...

See all answers

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.

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

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

Dataloader.io vs DBamp

Compared 33% of the time

MuleSoft Anypoint Platform vs DBamp

Compared 22% of the time

Skyvia vs DBamp

Compared 10% of the time

More DBamp Competitors

Product Reports

Buyer's Guide

Azure Data Factory

June 2026

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Buyer's Guide

Data Integration

June 2026

Download DBamp 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

DBamp is a versatile tool that simplifies Salesforce data integration directly within SQL Server, providing seamless access to Salesforce data with the ease of SQL queries.

DBamp bridges the gap between Salesforce and SQL Server, offering organizations the ability to query Salesforce data and metadata through standard SQL commands. This makes it easier for businesses to generate comprehensive reports and manage data exchange between Salesforce and SQL databases efficiently. With DBamp, businesses can enhance data analysis processes and ensure a more fluid data integration experience.

What are the most important features of DBamp?

Real-time Data Access: Access Salesforce data in real time without cumbersome data transfers.
Simple Integration: Use familiar SQL interfaces to manage Salesforce data integration.
Flexible Deployment: Supports diverse configurations to fit enterprise needs.
Automated Data Sync: Keep data between Salesforce and SQL in sync automatically.
Comprehensive Support: Offers reliable customer service for swift troubleshooting.

What benefits or ROI should users look for in reviews?

Streamlined Operations: Reduces time and resources spent on manual data extraction.
Enhanced Data Insights: Provides more accurate and timely business insights.
Cost Efficiency: Minimizes expenses related to custom data integration solutions.
Improved Accuracy: Ensures data fidelity and reduces error margins.
Time Savings: Accelerates data processing and decision-making.

In industries like finance, DBamp is used to integrate Salesforce with SQL Server, improving financial reporting accuracy. Retail sectors benefit from real-time inventory updates by syncing Salesforce customer data directly into SQL databases. Healthcare institutions leverage DBamp for effective patient record management by connecting Salesforce and SQL storage solutions seamlessly.

CData Software

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: June 2026.

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