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Azure Data Factory vs WhereScape RED comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Number of Reviews
85
Ranking in other categories
Cloud Data Warehouse (3rd)
WhereScape RED
Ranking in Data Integration
49th
Average Rating
8.2
Number of Reviews
15
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.1%, down from 13.3% compared to the previous year. The mindshare of WhereScape RED is 1.0%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Camilo Velasco - PeerSpot reviewer
Oct 27, 2022
No deployment cost, quick implementation, pay only for the processing time and data
The primary use case of this solution is to extract ETLS, transform and load data, and organize database synchronization The most valuable feature of this solution is the data flow, which is the same SQL server in important service, integration services, which is a very robust and powerful tool…
SM
Jul 9, 2021
Quick to set up, flexible, and stable
The scheduling part I don't like due to the fact that it allows you to schedule as a parent and child and other things, however, the error trackability has to be a little more user-friendly. It's also not user-friendly in the sense that it loads all the jobs and there are not enough filters so that it doesn't need to load everything. If the job fails, you don't get any type of alert or email. It would be ideal if there was some sort of automated alert message. Technical support isn't the best. It would be ideal if we understood how to do it in a card exception regarding exclusion, where the card is captured separately rather than filling the whole process on the data inbound side. Certain workloads like this are organized in such a way where you seem to be doubling the work as opposed to streamlining the process.

Quotes from Members

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

Pros

"The most valuable feature is the copy activity."
"The trigger scheduling options are decently robust."
"We use the solution to move data from on-premises to the cloud."
"The scalability of the product is impressive."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"I like the basic features like the data-based pipelines."
"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."
"The tool supports multiple target update methods."
"The most valuable feature is the metadata generated code."
"I found the initial setup very easy."
"Naturally produces a way to easily debug your DW data solutions."
"Data transformations and rollups are easy to accomplish."
"I like the data vault implementations."
"This is a fantastically robust DW tool that will make you at least 10 times faster in producing a DW."
"Support is absolutely excellent, efficient, and timely."
 

Cons

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"The deployment should be easier."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"Some known bugs and issues with Azure Data Factory could be rectified."
"The one element of the solution that we have used and could be improved is the user interface."
"There aren't many third-party extensions or plugins available in the solution."
"The setup and configuration process could be simplified."
"The ability to execute SSIS projects within WhereScape would be nice because we have a lot of packages that are too cumbersome to recreate."
"It could use a tool to diagnose what is missing from the environment for WhereScape to install successfully."
"The scheduled jobs which are run by the WhereScape scheduler seem to be a strangely separate animal. Unlike all other WhereScape objects, jobs cannot be added to WhereScape projects. Also, unlike all other objects, jobs also cannot be deleted using a WhereScape deployment application."
"Improve the object renaming ability (it works, but it could be more automated)."
"Project-based searching of data objects in the data warehouse browser needs to be improved."
"The solution can be a little more user-friendly on enterprise-level where people use it."
"Jobs cannot be deleted via the deployment package. When deploying from dev to QA or production, a job has to be retired. The job has to be manually removed from the target environment."
"No support for change data capture or delta detection - that must be custom coded ."
 

Pricing and Cost Advice

"The price is fair."
"ADF is cheaper compared to AWS."
"Data Factory is affordable."
"The solution is cheap."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"The licensing cost is included in the Synapse."
"I would not say that this product is overly expensive."
"Factor in the price of specialized consulting who know this product. They're hard to find and expensive."
"Our company purchased a corporate unlimited license."
"Speed to market of a warehouse solution at a relatively inexpensive price point."
"ROI is at least 10 times."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
13%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
17%
Government
10%
Insurance Company
9%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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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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
British American Tobacco, Cornell University, Allianz Benelux, Finnair, Solarwinds and many more.
Find out what your peers are saying about Azure Data Factory vs. WhereScape RED and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.