Azure Data Factory vs Precisely Connect comparison

Why PeerSpot?

Microsoft and Precisely are both solutions in the Data Integration category. Microsoft is ranked #5 with an average rating of 8.0, while Precisely is ranked #45 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

14,793 Views
10,207 Comparison Views

92% willing to recommend

Precisely Connect

Read 1 Precisely Connect review

2,037 Views
1,670 Comparison Views

100% willing to recommend

Azure Data Factory

Precisely Connect

Comparison Buyer's Guide

Download the report

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, Palantir, Microsoft and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: September 2026).

Buyer's Guide

Data Integration

September 2026

Download the complete report

Helped 913,683 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

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 September 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 5.5% compared to the previous year. The mindshare of Precisely Connect is 0.7%, up from 0.5% 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.

Read full review

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…

Read full review

Quotes from Members

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

Pros

"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 most valuable feature is the ease in which you can create an ETL pipeline."

"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."

"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."

"The solution can scale very easily."

"It's extremely consistent."

"Azure Data Factory is great because it's a cloud service; you do not have to take care of the installation and configuration yourself."

"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."

More Azure Data Factory pros

"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

"When we initiated the cluster, it took some time to start the process."

"When the record fails, it's tough to identify and log."

"The speed and performance need to be improved."

"To my mind, the solution needs to be more connectable to its own services."

"In the next release, it's important that some sort of scheduler for running tasks is added."

"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."

"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."

"When working with AWS, we have noticed that the difference between ADF and AWS is that AWS is more customer-focused. They're more responsive compared to any other company. ADF is not as good as AWS, but it should be. If AWS is ten out of ten, ADF is around eight out of ten. I think AWS is easier to understand from the GUI perspective compared to ADF."

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

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

"Data Factory is expensive."

"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."

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

"Pricing is comparable, it's somewhere in the middle."

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

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"The price is fair."

More Azure Data Factory pricing and cost advice

Information not available

See which vendors are best for you

Use our free recommendation engine to learn which Data Integration solutions are best for your needs.

See recommendations

913,683 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

11%

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	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...

See all answers

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...

See all answers

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 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 18% of the time

Qlik Talend Cloud vs Precisely Connect

Compared 13% 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

September 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

September 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, Palantir, Microsoft and others in Data Integration. Updated: September 2026.

DOWNLOAD NOW

913,683 professionals have used our research since 2012.

See our list of best Data Integration vendors.

We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.