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Azure Data Factory vs TIBCO Scribe comparison

 

Comparison Buyer's Guide

Executive Summary

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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
TIBCO Scribe
Ranking in Data Integration
50th
Average Rating
6.0
Reviews Sentiment
6.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.0%, down from 9.8% compared to the previous year. The mindshare of TIBCO Scribe is 0.5%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.0%
TIBCO Scribe0.5%
Other96.5%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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.
GouravSuri - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"The data is more scalable."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."
"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"In terms of my personal experience, it works fine."
"It is beneficial that the solution is written with Spark as the back end."
"The most valuable feature of TIBCO Scribe is the connectors available to various products."
 

Cons

"We require Azure Data Factory to be able to connect to Google Analytics."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score."
"Some prebuilt data source or data connection aspects are generic."
"They should work on optimizing their licensing model and pricing structure."
"I do not have any notes for improvement."
"Data Factory's performance during heavy data processing isn't great."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"The solution should provide better documentation and scenario-based samples."
 

Pricing and Cost Advice

"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."
"Understanding the pricing model for Data Factory is quite complex."
"The pricing model is based on usage and is not cheap."
"The price is fair."
"Data Factory is expensive."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"Product is priced at the market standard."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Computer Software Company
19%
Manufacturing Company
11%
Financial Services Firm
8%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
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.
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...
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...
What do you like most about TIBCO Scribe?
The most valuable feature of TIBCO Scribe is the connectors available to various products.
What needs improvement with TIBCO Scribe?
The solution should provide better documentation and scenario-based samples.
What is your primary use case for TIBCO Scribe?
TIBCO Scribe is used to do some out-of-the-box integration with some packaged products. TIBCO Scribe is a cloud solution that has a lot of connectors, like REST connectors and database connectors t...
 

Also Known As

No data available
Scribe
 

Overview

 

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 Microsoft, Informatica, IBM and others in Data Integration. Updated: January 2026.
881,733 professionals have used our research since 2012.