Azure Data Factory vs TIBCO Scribe comparison

Microsoft and TIBCO are both solutions in the Data Integration category. Microsoft is ranked #4 with an average rating of 8.2, while TIBCO is ranked #62. Microsoft holds a 2.4% 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 94 Azure Data Factory reviews

12,241 Views
8,446 Comparison Views

92% willing to recommend

TIBCO Scribe

Read 1 TIBCO Scribe review

1,232 Views
936 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, Qlik and others in Data Integration.

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

Buyer's Guide

Data Integration

May 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

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (5th)

TIBCO Scribe

Ranking in Data Integration

62nd

Average Rating

6.0

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.4%, down from 8.6% compared to the previous year. The mindshare of TIBCO Scribe is 0.6%, 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	2.4%
TIBCO Scribe	0.6%
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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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

"It's extremely consistent."

"It has big potential, especially as a PaaS offering."

"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."

"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS"

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"The data flows were beneficial, allowing us to perform multiple transformations."

"The best part of this product is the extraction, transformation, and load."

"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."

More Azure Data Factory pros

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

Cons

"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"The performance and stability are touch and go."

"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations."

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."

"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."

"Data Factory's cost is too high."

"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."

More Azure Data Factory cons

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

Pricing and Cost Advice

"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."

"Product is priced at the market standard."

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

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

"The licensing is a pay-as-you-go model, where you pay for what you consume."

"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."

"The solution is cheap."

"It's not particularly 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

12%

Computer Software Company

10%

Manufacturing Company

Government

Computer Software Company

17%

Manufacturing Company

12%

Construction Company

11%

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	20
Large Enterprise	57

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...

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Comparisons

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

Compared 5% of the time

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 3% 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

SSIS vs TIBCO Scribe

Compared 15% of the time

Oracle Data Integrator (ODI) vs TIBCO Scribe

Compared 10% of the time

WSO2 Enterprise Integrator vs TIBCO Scribe

Compared 9% of the time

IBM App Connect vs TIBCO Scribe

Compared 8% of the time

Informatica PowerCenter vs TIBCO Scribe

Compared 7% of the time

More TIBCO Scribe Competitors

Product Reports

Buyer's Guide

Azure Data Factory

May 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

May 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

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