Azure Data Factory vs TIBCO Scribe comparison

Why PeerSpot?

Microsoft and TIBCO are both solutions in the Data Integration category. Microsoft is ranked #5 with an average rating of 8.0, while TIBCO is ranked #66. 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

14,793 Views
10,207 Comparison Views

92% willing to recommend

TIBCO Scribe

Read 1 TIBCO Scribe review

1,790 Views
1,360 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, 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

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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)

TIBCO Scribe

Ranking in Data Integration

66th

Average Rating

6.0

Reviews Sentiment

6.2

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 TIBCO Scribe is 0.6%, up from 0.4% 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

"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."

"This is an excellent tool for pipeline orchestration; connecting the different components and activities as well as gathering data."

"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."

"The overall performance is quite good."

"The features that I've found most valuable, in order: That it is a complete ETL Solution, the second one is interface, the third one workflow, and the fourth one ease of use."

"I like that it's a monolithic data platform. This is why we propose these solutions."

"The user interface is very good. It makes me feel very comfortable when I am using the tool."

"Azure Data Factory is easy to use and integrates well, providing good classification to bring data from diverse parts of the data infrastructure, whether from CSV files coming from the Cisco server, MySQL, Excel machines, or local network data from remote files."

More Azure Data Factory pros

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

Cons

"They should work on optimizing their licensing model and pricing structure."

"Azure Data Factory didn't bring a lot of good when we were also using Alteryx."

"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."

"Some of the optimization techniques are not scalable."

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

"Additionally, the ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features."

"The stability of Azure as a PaaS could be improved."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

More Azure Data Factory cons

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

Pricing and Cost Advice

"The cost is based on the amount of data sets that we are ingesting."

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"ADF is cheaper compared to AWS."

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

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

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

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

"Data Factory is expensive."

More Azure Data Factory pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Computer Software Company

17%

Manufacturing Company

12%

Construction Company

11%

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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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

Informatica PowerCenter vs TIBCO Scribe

Compared 8% of the time

Oracle Data Integrator (ODI) vs TIBCO Scribe

Compared 8% of the time

Pentaho Data Integration and Analytics vs TIBCO Scribe

Compared 7% of the time

WSO2 Enterprise Integrator vs TIBCO Scribe

Compared 6% of the time

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

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