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Azure Data Factory vs TIBCO Live Datamart 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
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (3rd)
TIBCO Live Datamart
Average Rating
9.0
Reviews Sentiment
7.0
Number of Reviews
2
Ranking in other categories
Data Warehouse (24th)
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
Mohsin Pathan - PeerSpot reviewer
Standout features are real-time dashboards and powerful aggregation
This product has a powerful aggregating feature which is great. It also has its own APIs. Whenever the data comes in, it can be streamed out anywhere. It's the only solution that provides real-time dashboards. Tableau doesn't have this feature. The three variants of historical data, real-time data and predicted data from Spitfire, give more strength to LiveDatamart without any dependency on other products. The product is easy to set up with very low maintenance required.

Quotes from Members

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

Pros

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"The overall performance is quite good."
"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."
"The function of the solution is great."
"We have been using drivers to connect to various data sets and consume data."
"The most important feature is that it can help you do the multi-threading concepts."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"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."
"The solution has a powerful aggregating feature"
"You can create your own rules that include mathematic calculations."
 

Cons

"Azure Data Factory's pricing in terms of utilization could be improved."
"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"I do not have any notes for improvement."
"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."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"Improvements need to be made on the load balancing side."
"The solution's setup could be quicker and easier."
 

Pricing and Cost Advice

"It's not particularly expensive."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"The cost is based on the amount of data sets that we are ingesting."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"This is a cost-effective solution."
"The price is fair."
"I would rate Data Factory's pricing nine out of ten."
"The solution might be considered a bit expensive because it competes with open-source products."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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
Streambase, TIBCO LiveView Data Mart
 

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
Aerospace Corporation, Balfour Beatty Infrastructure Services, Banco Sabadell, Bolton Borough Council
Find out what your peers are saying about Azure Data Factory vs. TIBCO Live Datamart and other solutions. Updated: March 2025.
846,617 professionals have used our research since 2012.