Azure Data Factory vs TIBCO Scribe comparison

Why PeerSpot?

Microsoft and TIBCO are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while TIBCO is ranked #64. Microsoft holds a 2.2% mindshare in DI, compared to TIBCO’s 0.6% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution.

Azure Data Factory

Read 97 Azure Data Factory reviews

16,078 Views
11,255 Comparison Views

92% willing to recommend

TIBCO Scribe

Read 1 TIBCO Scribe review

2,140 Views
1,669 Comparison Views

0% willing to recommend

Azure Data Factory

TIBCO Scribe

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and TIBCO Scribe 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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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)

TIBCO Scribe

Ranking in Data Integration

64th

Average Rating

6.0

Reviews Sentiment

6.2

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 TIBCO Scribe is 0.6%, 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%
TIBCO Scribe	0.6%
Other	97.2%

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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GouravSuri

Software Engineer (L4) at Uber

A cloud solution that has a lot of connectors, but it should provide better documentation and scenario-based samples

Smaller customers who want to integrate with other systems don't need too much in-house expertise in terms of technology. They can hire consultants who can implement this solution for them, and they don't have to maintain any infrastructure. For a smaller setup, it is a go-to integration system wherein they don't need a lot of expertise or infrastructure. The solution's UI is pretty intuitive and easy. It is good for smaller integration use cases. I think it would be a problem for bigger use cases. Overall, I rate TIBCO Scribe a six out of ten.

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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

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."

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

"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."

"Powerful but easy-to-use and intuitive."

"The most valuable part of this product is the ease of use, as it is easy to use and rather intuitive, and because it is easy to use, you can do things with it easily, making your work easier and therefore more valuable."

"From my experience so far, the best feature is the ability to copy data to any environment. We have 100 connects and we can connect them to the system and copy the data from its respective system to any environment. That is the best feature."

"The most important feature is that it can help you do the multi-threading concepts."

More Azure Data Factory pros

"The most valuable feature of TIBCO Scribe is the connectors available to various products."

Cons

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"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."

"I would like to see this time travel feature in Snowflake added to Azure Data Factory."

"The speed and performance need to be improved."

"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."

"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."

"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."

"Azure Data Factory uses many resources and has issues with parallel workflows."

More Azure Data Factory cons

"The solution should provide better documentation and scenario-based samples."

Pricing and Cost Advice

"The pricing model is based on usage and is not cheap."

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

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

"The licensing cost is included in the Synapse."

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

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

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

"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."

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

17%

Comms Service Provider

12%

Construction Company

11%

Manufacturing Company

11%

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.

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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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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

SSIS vs TIBCO Scribe

Compared 15% of the time

Oracle Data Integrator (ODI) vs TIBCO Scribe

Compared 9% of the time

Pentaho Data Integration and Analytics vs TIBCO Scribe

Compared 9% of the time

Informatica PowerCenter vs TIBCO Scribe

Compared 8% of the time

SharePlex vs TIBCO Scribe

Compared 5% of the time

More TIBCO Scribe 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 TIBCO Scribe product report

Also Known As

No data available

Scribe

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

TIBCO Scribe is an integration service designed to streamline data connectivity across diverse applications, offering a comprehensive framework for efficient data management and workflow automation.

Engineered to empower data-driven strategies, TIBCO Scribe facilitates intuitive mapping and transformation of data, enabling seamless collaboration between cloud and on-premises systems. It addresses complex data challenges, reducing time and resources needed for integration tasks. Users benefit from its adaptability and scalability, making it suitable for diverse data environments.

What are the key features of TIBCO Scribe?

Data Integration: Seamlessly connects various applications for streamlined data flow.
Visual Mapping: Offers intuitive tools for data transformation and mapping workflows.
Pre-built Connectors: Provides an array of connectors for major applications, accelerating integration processes.
Cloud and On-Premises Support: Ensures integration capabilities extend across infrastructure landscapes.
Error Management: Features robust error monitoring and handling for consistent data operations.

What benefits should users consider in TIBCO Scribe reviews?

Efficiency: Significant reduction in integration time and resource allocation.
Scalability: Easily scales with growing business needs, accommodating increasing data volume.
Flexibility: Supports diverse integration scenarios, adapting to specific data architectures.
Cost-Effectiveness: Potential reduction in overall integration costs through efficient processes.

Industry use of TIBCO Scribe varies widely, with notable implementations in sectors such as finance where it supports real-time transaction processing, and healthcare, facilitating patient data integration for enhanced care delivery. Its capabilities are central to optimizing data strategies across these industries.

TIBCO

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

Armanino, Oklahoma City Thunder, Texas Rangers, Tata Technologies, BenefAction, Indianapolis Motor Speedway, Atdec, Dynasplint Systems

Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: October 2026.

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