Azure Data Factory vs Precisely Connect comparison

Why PeerSpot?

Microsoft and Precisely are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while Precisely is ranked #48 with an average rating of 8.0. Microsoft holds a 2.2% mindshare in DI, compared to Precisely’s 0.7% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Precisely users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

16,078 Views
11,255 Comparison Views

92% willing to recommend

Precisely Connect

Read 1 Precisely Connect review

2,420 Views
2,033 Comparison Views

100% willing to recommend

Azure Data Factory

Precisely Connect

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and Precisely Connect 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: October 2026).

Buyer's Guide

Data Integration

October 2026

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Helped 920,769 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

6th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

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

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
Product	Mindshare (%)
Azure Data Factory	2.2%
Precisely Connect	0.7%
Other	97.1%

Data Integration

Featured Reviews

Kunal Das

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.

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reviewer2667306

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…

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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

"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."

"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."

"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."

"The trigger scheduling options are decently robust."

"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."

"The data copy template is a valuable feature, and with the pipeline template, it takes only a few clicks for the on-premises data to come in."

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."

More Azure Data Factory pros

"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

"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."

"Some prebuilt data source or data connection aspects are generic."

"It would be better if it had machine learning capabilities."

"I have not found any real shortcomings within the product."

"There are performance issues, particularly with the underlying compute, which should be configurable."

"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."

"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."

"The one element of the solution that we have used and could be improved is the user interface."

More Azure Data Factory cons

"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

"Product is priced at the market standard."

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

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

"It's not particularly expensive."

"I would rate Data Factory's pricing nine out of ten."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

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

More Azure Data Factory pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Manufacturing Company

11%

Financial Services Firm

10%

Outsourcing Company

Computer Software Company

Financial Services Firm

11%

Construction Company

11%

Outsourcing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

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 Precisely Connect?

Precisely has a high entry price, which is why it is not suitable for small to mid-sized organizations.

See all answers

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.

See all answers

What is your primary use case for Precisely Connect?

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Comparisons

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

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

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Oracle Data Integrator (ODI) vs Precisely Connect

Compared 20% of the time

Qlik Talend Cloud vs Precisely Connect

Compared 12% of the time

Informatica PowerCenter vs Precisely Connect

Compared 11% of the time

SSIS vs Precisely Connect

Compared 9% of the time

More Precisely Connect Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

October 2026

Download Precisely Connect product report

Also Known As

No data available

DMExpress, Syncsort DMX, Syncsort Connect ETL

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

Precisely Connect is a robust data integration solution designed for seamless data connectivity across diverse platforms. It offers impressive capabilities to manage and analyze data efficiently, delivering great value for businesses aiming to optimize data-driven decision-making processes.

Precisely Connect stands out by providing comprehensive integration options for heterogenous data environments. Its user-friendly design and extensive functionality make it an ideal choice for businesses looking to harness the full potential of their data assets. Its flexibility and support for a wide range of data sources simplify the task of managing complex data landscapes. By enabling efficient data movement and transformation, it empowers enterprises to derive meaningful insights and drive strategic initiatives effectively.

What are the main features of Precisely Connect?

Data Integration: Effortlessly connects various data sources, ensuring seamless data flow and accuracy.
Scalability: Adapts to growing business needs while maintaining performance and reliability.
Real-time Data Processing: Supports immediate data gathering and analysis for timely decision-making.
Comprehensive Support: Includes extensive documentation and customer service for end-user ease.

What benefits should users expect?

Increased Efficiency: Streamlined processes reduce time and labor costs associated with data management.
Enhanced Insight: Greater access to integrated data leads to informed business strategies.
Cost Savings: Minimizes infrastructure costs by optimizing data operations and reducing resource consumption.
Improved Decision Making: Facilitates data-driven decisions with reliable and up-to-date information.

In industries such as finance and healthcare, Precisely Connect is implemented to ensure data integrity and compliance, crucial for regulatory mandates. Retail businesses leverage its capabilities to analyze consumer data for personalized marketing strategies, while manufacturing companies utilize it for optimizing supply chain operations and inventory management.

Precisely

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.

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