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Azure Data Factory vs Precisely Connect 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
97
Ranking in other categories
Cloud Data Warehouse (7th)
Precisely Connect
Ranking in Data Integration
45th
Average Rating
8.0
Reviews Sentiment
6.3
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 Precisely Connect is 0.7%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.3%
Precisely Connect0.7%
Other97.0%
Data Integration
 

Featured Reviews

Kunal Das - PeerSpot reviewer
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.
reviewer2667306 - PeerSpot reviewer
Data Engineer at a consultancy with 1-10 employees
AI compliance integration elevates data quality and decision-making
I usually implement Precisely and Collibra tools for clients to enhance data quality. My main use case involves working with the data catalog of Precisely to integrate data management processes and ensure data governance Precisely has the AI Act already implemented into the data catalog, which…

Quotes from Members

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

Pros

"It's extremely consistent."
"The most valuable features are data transformations."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"The solution has a good interface and the integration with GitHub is very useful."
"It is beneficial that the solution is written with Spark as the back end."
"If you have Azure as a cloud service and you want to perform ETL then Azure Data Factory is a product that I can recommend."
"It's a good tool, a good product that does what it's supposed to do well, which is ingesting data from a source to your target, to another cloud, to another source."
"Precisely has the AI Act already implemented into the data catalog, which allows the integration of the European Artificial Intelligence Act into our processes."
"Using Precisely improves data quality, which can lead to a 30% increase in revenue and boost net income by 20% to 25% if implemented correctly."
 

Cons

"The Microsoft documentation is too complicated."
"Some known bugs and issues with Azure Data Factory could be rectified."
"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."
"Compared to Informatica, it's really crude. I think it's a very crude solution."
"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."
"There's space for improvement in the development process of the data pipelines."
"We require Azure Data Factory to be able to connect to Google Analytics."
"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."
"Precisely works with a tool called Analyze, which has a steep learning curve due to its use of Jython, a combination of Java and Python. This could be improved to make the tool more user-friendly."
 

Pricing and Cost Advice

"The solution's pricing is competitive."
"The pricing is a bit on the higher end."
"The price you pay is determined by how much you use it."
"Data Factory is affordable."
"Pricing appears to be reasonable in my opinion."
"The cost is based on the amount of data sets that we are ingesting."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
8%
Construction Company
7%
Financial Services Firm
15%
Construction Company
12%
Insurance Company
10%
Outsourcing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise64
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 Precisely Connect?
Precisely has a high entry price, which is why it is not suitable for small to mid-sized organizations.
What needs improvement with Precisely Connect?
Precisely works with a tool called Analyze, which has a steep learning curve due to its use of Jython, a combination of Java and Python. This could be improved to make the tool more user-friendly.
What is your primary use case for Precisely Connect?
I usually implement Precisely and Collibra tools for clients to enhance data quality. My main use case involves working with the data catalog of Precisely to integrate data management processes and...
 

Also Known As

No data available
DMExpress, Syncsort DMX, Syncsort Connect ETL
 

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
Hermes, Kantar Worldpanel, Kojima Press Industry Co. Ltd., OTC Markets Group, Experian, Co-operative Group, State of Tennessee Department of Human Services, Centers for Medicare & Medicaid Services, Silverton, comScore
Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: August 2026.
910,437 professionals have used our research since 2012.