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Azure Data Factory vs Workato 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:
 

ROI

Sentiment score
7.1
Azure Data Factory offers significant time, effort, and infrastructure savings, enhancing data analysis and decision-making capabilities.
Sentiment score
7.9
Workato simplifies app integration, boosting productivity and cost savings, with visible results often seen within a week.
By replacing multiple legacy systems and teams with a single automated platform, organizations see significant cost savings and improved business operations.
In my experience, we have seen a return on investment, with results visible within a week.
 

Customer Service

Sentiment score
6.5
Azure Data Factory support is praised for responsiveness, though some report delays; satisfaction varies with Microsoft partnerships.
Sentiment score
7.8
Workato's customer service earns praise for responsiveness, real-time support, and community engagement, despite limited availability and product challenges.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The technical support for Azure Data Factory is generally acceptable.
Whenever we faced issues with data volume, the support team helped us by suggesting solutions like breaking the data into chunks.
I reach out to the professional services team or customer success team for technical support, and they provide immediate responses.
Workato's support is robust, featuring first and second-level support.
 

Scalability Issues

Sentiment score
7.5
Azure Data Factory scales efficiently, managing large datasets for enterprises, though users note cost and integration limitations.
Sentiment score
6.9
Workato offers scalable and elastic operations, supporting multi-region use but may face issues with higher data volumes.
Azure Data Factory is highly scalable.
There are scalability limitations with Workato.
Allows dynamic connection switching at runtime.
Even when clients overutilize the product, Workato allows them to continue without interruption, charging accordingly rather than limiting usage.
 

Stability Issues

Sentiment score
7.8
Azure Data Factory is highly rated for stability, scalability, and performance, despite occasional minor issues with larger data volumes.
Sentiment score
7.6
Workato is highly rated for stability and reliability, though occasional high-load issues require extra maintenance efforts.
The solution has a high level of stability, roughly a nine out of ten.
Once deployed, solutions do not break, making it more reliable than other solutions like Microsoft Power Automate that often disconnect.
During the initial data loads with large volumes, Workato was unable to handle the data effectively, which indicates stability issues under high loads.
To handle more than 50,000 records, I use scripting actions like Python or JavaScript to process large data in chunks.
 

Room For Improvement

Azure Data Factory requires improvements in integration, pricing, documentation, UI, monitoring, processing, and debugging for enhanced user experience.
Workato needs improvements in collaboration, scalability, API management, licensing clarity, security, and more community recipes and connectors.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
There is a problem with the integration with third-party solutions, particularly with SAP.
Workato struggles with scalability when handling high volumes of data, such as terabytes, requiring chunking for initial data loads.
One area for improvement is the CI/CD pipeline, which lacks a version control system similar to GitHub for easier deployment.
Currently, there's no way to set breakpoints to stop the process and debug an error as you can in other tools like webMethods.
 

Setup Cost

Azure Data Factory offers competitive, flexible pay-as-you-go pricing; costs vary by data volume and use of additional services.
Workato offers competitive enterprise pricing, benefiting users with bundled connectors and flexible, consumption-based models without hidden fees.
The pricing is cost-effective.
It is considered cost-effective.
While the upfront cost is high due to task-based pricing, the cost is relatively low in terms of development because Workato provides necessary connectors for integration use cases.
Compared to other iPaaS solutions like Boomi, Workato’s pricing model charges per connection step, which increases the cost.
Workato's pay-as-you-use model is competitive when compared with other iPaaS providers, making it cost-effective for organizations looking to integrate multiple functionalities under one platform.
 

Valuable Features

Azure Data Factory enables easy data integration, management, and transformation with over 100 connectors, supporting ETL and automation efficiently.
Workato simplifies app integration with drag-and-drop UI, enabling efficient automation for non-technical users across industries.
It connects to different sources out-of-the-box, making integration much easier.
The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with.
I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets.
It allows app-to-app and real-time integrations, which significantly enhance process efficiency.
It comes with pre-built connectors, eliminating the need to write APIs.
The platform's ease of use for connecting to different integrations, like Salesforce and NetSuite, is very beneficial because development isn't necessary, and everything is readily available.
 

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)
Workato
Average Rating
8.4
Reviews Sentiment
7.1
Number of Reviews
17
Ranking in other categories
Integration Platform as a Service (iPaaS) (8th)
 

Mindshare comparison

Azure Data Factory and Workato aren’t in the same category and serve different purposes. Azure Data Factory is designed for Data Integration and holds a mindshare of 8.9%, down 12.5% compared to last year.
Workato, on the other hand, focuses on Integration Platform as a Service (iPaaS), holds 4.3% mindshare, up 4.2% since last year.
Data Integration
Integration Platform as a Service (iPaaS)
 

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.
Rohit Sircar - PeerSpot reviewer
Great automation and strong workflows useful for integration
The initial setup is quite straightforward. When connecting Workato with your on-premises system, you have to install the Workato agent on your network. It was not complex but a long process to configure and settle. Workato has not gone live for us yet, so only the developers are currently using it. But in terms of users, we will have close to 250 and maybe 30 additional direct users. We are seeing a lot of different use cases where we can add new recipes because we started small, and there are many different areas where we can implement Workato for automation.
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Educational Organization
33%
Financial Services Firm
10%
Computer Software Company
9%
Manufacturing Company
7%
 

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...
What do you like most about Workato?
Workato is low code, intuitive, and easy to use.
What needs improvement with Workato?
One area for improvement is the CI/CD pipeline, which lacks a version control system similar to GitHub ( /products/github-reviews ) for easier deployment. Though it has a recipe life cycle manageme...
What is your primary use case for Workato?
I am using Workato ( /products/workato-reviews ) for integrating and automating solutions for finance, HR, and IT. Specific use cases include onboarding and offboarding for HR, handling invoices fo...
 

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
Panera Bread, Berkshire Hathaway, Salesforce, Box, Splunk, ComScore, IBM, Complex Media, Microsoft, Home Depot, Cisco, News Corp, Braille Institute
Find out what your peers are saying about Azure Data Factory vs. Workato and other solutions. Updated: May 2023.
849,686 professionals have used our research since 2012.