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Azure Data Factory vs Precisely Connect comparison

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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
6th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
97
Ranking in other categories
Cloud Data Warehouse (8th)
Precisely Connect
Ranking in Data Integration
48th
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 November 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 4.4% compared to the previous year. The mindshare of Precisely Connect is 0.7%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.2%
Precisely Connect0.7%
Other97.1%
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 is very modular; it works well, is very flexible, and you can easily bring in outside capabilities and build any features you want."
"The overall architecture has been very valuable to us, as it has allowed us to scale up pretty rapidly."
"The data flows were beneficial, allowing us to perform multiple transformations."
"Since I have mentioned that I can use the drag-and-drop activities, by using that, Azure Data Factory is saving a lot of time, my organization has already been saving the time and generating more income with that."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"The flexibility that Azure Data Factory offers is great."
"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."
"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

"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"Areas for improvement would be the product's performance and its mapping of data flow."
"The pricing model should be more transparent and available online."
"Data Factory's monitorability could be better."
"We have experienced some issues with the integration. This is an area that needs improvement."
"Understanding the pricing model for Data Factory is quite complex. It needs to be simplified, and easier to understand."
"The product could provide more ways to import and export data."
"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."
"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

"This is a cost-effective solution."
"The cost is based on the amount of data sets that we are ingesting."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"The licensing cost is included in the Synapse."
"I would not say that this product is overly expensive."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"Product is priced at the market standard."
Information not available
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Top Industries

By visitors reading reviews
Manufacturing Company
11%
Financial Services Firm
10%
Outsourcing Company
8%
Computer Software Company
7%
Financial Services Firm
11%
Construction Company
11%
Outsourcing Company
9%
Comms Service Provider
9%
 

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: October 2026.
920,769 professionals have used our research since 2012.