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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
4th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
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
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 8.1% 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
ProductMindshare (%)
Azure Data Factory2.3%
TIBCO Scribe0.6%
Other97.1%
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

"Azure Data Factory is a good tool."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"I like the basic features like the data-based pipelines."
"The solution has a good interface and the integration with GitHub is very useful."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"The most valuable feature of this solution is that it allows more data between on-premises and cloud solutions."
"The most valuable feature of TIBCO Scribe is the connectors available to various products."
 

Cons

"The product's technical support has certain shortcomings, making it an area where improvements are required."
"The stability of Azure as a PaaS could be improved."
"They should work on optimizing their licensing model and pricing structure."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"But, I feel that if the usage extends beyond a certain threshold, it will start getting expensive."
"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."
"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."
"Azure Data Factory's pricing in terms of utilization could be improved."
"The solution should provide better documentation and scenario-based samples."
 

Pricing and Cost Advice

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"The solution's pricing is competitive."
"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."
"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."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"The pricing is a bit on the higher end."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Construction Company
6%
Computer Software Company
17%
Manufacturing Company
12%
Construction Company
11%
Outsourcing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
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...
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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 Informatica, Microsoft, Palantir and others in Data Integration. Updated: June 2026.
900,747 professionals have used our research since 2012.