No more typing reviews! Try our Samantha, our new voice AI agent.

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
96
Ranking in other categories
Cloud Data Warehouse (7th)
Precisely Connect
Ranking in Data Integration
44th
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 July 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.6% 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

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.
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

"The solution has a good interface and the integration with GitHub is very useful."
"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."
"The user interface is very good. It makes me feel very comfortable when I am using the tool."
"The most valuable features are data transformations."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"It is very modular; it works well, is very flexible, and you can easily bring in outside capabilities and build any features you want."
"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"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."
"Precisely has the AI Act already implemented into the data catalog, which allows the integration of the European Artificial Intelligence Act into our processes."
 

Cons

"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"The stability of Azure as a PaaS could be improved."
"The main challenge with implementing Azure Data Factory is that it processes data in batches, not near real-time. To achieve near real-time processing, we need to schedule updates more frequently, which can be an issue. Its interface needs to be lighter."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"Some prebuilt data source or data connection aspects are generic."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"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

"I don't see a cost; it appears to be included in general support."
"The price is fair."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"Pricing appears to be reasonable in my opinion."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"I would not say that this product is overly expensive."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"This is a cost-effective solution."
Information not available
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
903,118 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Construction Company
6%
Financial Services Firm
15%
Construction Company
12%
Insurance Company
11%
Outsourcing Company
8%
 

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 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: June 2026.
903,118 professionals have used our research since 2012.