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 8.2, while CData Software is ranked #48 with an average rating of 8.0. Microsoft holds a 2.4% 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 94 Azure Data Factory reviews

12,241 Views
8,446 Comparison Views

92% willing to recommend

DBamp

Read 1 DBamp review

732 Views
666 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, Qlik and others in Data Integration.

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

Buyer's Guide

Data Integration

May 2026

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Helped 893,244 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

6.8

Number of Reviews

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

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
Product	Mindshare (%)
Azure Data Factory	2.4%
DBamp	0.4%
Other	97.2%

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

"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."

"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface, so that eases the entire process."

"We have found the bulk load feature very valuable."

"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."

"I like that it's a monolithic data platform. This is why we propose these solutions."

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

"I like the basic features like the data-based pipelines."

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

More Azure Data Factory pros

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

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

Cons

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

"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."

"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."

"Compared to Informatica, it's really crude. I think it's a very crude solution."

"When we initiated the cluster, it took some time to start the process."

"Data Factory's cost is too high."

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score."

More Azure Data Factory cons

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

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 price you pay is determined by how much you use it."

"Understanding the pricing model for Data Factory is quite complex."

"Pricing appears to be reasonable in my opinion."

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

"The solution is cheap."

"The pricing is a bit on the higher end."

"This is a cost-effective solution."

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

10%

Manufacturing Company

Government

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	20
Large Enterprise	57

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...

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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

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

Compared 5% of the time

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 3% 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 30% of the time

MuleSoft Anypoint Platform vs DBamp

Compared 26% of the time

Skyvia vs DBamp

Compared 10% of the time

More DBamp Competitors

Product Reports

Buyer's Guide

Azure Data Factory

May 2026

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Buyer's Guide

Data Integration

May 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

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