Azure Data Factory vs Precisely Connect comparison

Microsoft and Precisely are both solutions in the Data Integration category. Microsoft is ranked #5 with an average rating of 7.9, while Precisely is ranked #45 with an average rating of 8.0. Microsoft holds a 2.3% 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 96 Azure Data Factory reviews

14,099 Views
9,728 Comparison Views

92% willing to recommend

Precisely Connect

Read 1 Precisely Connect review

1,787 Views
1,465 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: July 2026).

Buyer's Guide

Data Integration

July 2026

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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

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

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
Product	Mindshare (%)
Azure Data Factory	2.3%
Precisely Connect	0.7%
Other	97.0%

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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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

"I like Azure Data Factory, it works quite well."

"It is easy to deploy workflows and schedule jobs."

"I can do everything I want with SSIS and Azure Data Factory."

"The most valuable aspect is the copy capability."

"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."

"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."

"The most valuable feature of this solution would be ease of use."

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

"There aren't many third-party extensions or plugins available in the solution."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."

"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."

"We have experienced some issues with the integration. This is an area that needs improvement."

"The thing we missed most was data update, but this is now available as of two weeks ago."

"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."

"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."

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

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

"I would not say that this product is overly expensive."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"Pricing appears to be reasonable in my opinion."

"Product is priced at the market standard."

"I don't see a cost; it appears to be included in general support."

"The price is fair."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

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%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

15%

Construction Company

11%

Insurance Company

10%

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	63

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?

See all answers

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 4% 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

Oracle Data Integrator (ODI) vs Precisely Connect

Compared 19% of the time

Qlik Talend Cloud vs Precisely Connect

Compared 15% of the time

Informatica PowerCenter vs Precisely Connect

Compared 13% of the time

SSIS vs Precisely Connect

Compared 9% of the time

ETL Solutions Transformation Manager vs Precisely Connect

Compared 2% of the time

More Precisely Connect Competitors

Product Reports

Buyer's Guide

Azure Data Factory

August 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

July 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: July 2026.

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