Try our new research platform with insights from 80,000+ expert users

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
7.3
Azure Data Factory enhances efficiency, centralizes data, reduces costs, and improves data analysis, offering significant financial and operational benefits.
Sentiment score
7.8
Workato integration boosts cash flow and productivity, promises over 40% ROI, and encourages cost-efficient automation within a week.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
By replacing multiple legacy systems and teams with a single automated platform, organizations see significant cost savings and improved business operations.
For main recipes, there are charges, so by focusing on creating as many callable recipes as possible based on requirements, we can improve cost efficiency for the business.
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 responsive but varies in speed, with community resources and documentation aiding user satisfaction.
Sentiment score
7.8
Workato's customer service is praised for responsiveness and knowledge, though some users seek more support options and availability.
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 excels in scalability, efficiently managing workloads for any size, despite higher costs than alternatives.
Sentiment score
7.3
Workato is scalable, adaptable, and efficient for multi-region operations, handling varied workloads and multiple databases seamlessly.
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 stable and reliable, but faces integration challenges and requires enhancements to compete with top competitors.
Sentiment score
7.4
Workato is dependable with minimal downtime, praised for AWS foundation, though struggles with high loads and large datasets.
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 needs improved integration, better scheduling, enhanced UI, simplified pricing, more connectors, and responsive support.
Workato users desire improved collaboration, feature discoverability, API management, customization, scaling, and advanced integration capabilities globally.
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 pricing is usage-based and cost-effective, but large data volumes can lead to increased expenses.
Workato offers transparent pricing with customizable agreements, potentially high costs, and competitive value compared to other iPaaS solutions.
The pricing is cost-effective.
It is considered cost-effective.
Higher volume is less expensive, but in general, it is kind of pricey.
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.
 

Valuable Features

Azure Data Factory provides seamless data integration, robust transformations, scalability, and strong SAP support, praised for its ease of use.
Workato provides easy integration and automation with a no-code, user-friendly interface, enhancing efficiency and security for businesses.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
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.
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
7.0
Number of Reviews
91
Ranking in other categories
Data Integration (1st), Cloud Data Warehouse (2nd)
Workato
Average Rating
8.4
Reviews Sentiment
7.1
Number of Reviews
20
Ranking in other categories
Integration Platform as a Service (iPaaS) (7th)
 

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 7.9%, down 12.2% compared to last year.
Workato, on the other hand, focuses on Integration Platform as a Service (iPaaS), holds 4.8% mindshare, up 4.3% 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.
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
860,592 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
Educational Organization
17%
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
8%
 

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?
I am currently in the exploratory phase. While the cloud-native aspect is beneficial, having deployment options similar to MuleSoft would be a great additional feature. Their approach aims to remov...
What is your primary use case for Workato?
I have been using Workato for the past two years now. Our current project was doing automation earlier with workflows using MuleSoft. These have now been moved to Workato for integrating systems 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.
860,592 professionals have used our research since 2012.