Azure Data Factory vs Workato comparison

Read 9 Workato reviews

1,318 Views
763 Comparison Views

100% willing to recommend

Azure Data Factory

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Azure Data Factory and Workato based on real PeerSpot user reviews.

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Azure Data Factory vs. Workato Report (Updated: May 2023).

Azure Data Factory vs. Workato

May 2023

Download the complete report

Helped 824,053 peers since 2012

Categories and Ranking

Azure Data Factory

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Integration (1st), Cloud Data Warehouse (3rd)

Workato

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Integration Platform as a Service (iPaaS) (9th)

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 11.0%, down 13.3% compared to last year.
Workato, on the other hand, focuses on Integration Platform as a Service (iPaaS), holds 3.8% mindshare, down 4.8% since last year.

Data Integration

Integration Platform as a Service (iPaaS)

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.

Read full review

Rohit Sircar

Integration Solutions Lead | Digital Core Transformation Service Line at Hexaware Technologies Limited

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.

Read full review

Quotes from Members

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

Pros

"The most important feature is that it can help you do the multi-threading concepts."

"The overall performance is quite good."

"It is easy to integrate."

"We have been using drivers to connect to various data sets and consume data."

"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

"Most of our customers are Microsoft shops and prefer Azure Data Factory because they have good licensing options and a trust factor with Microsoft."

"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."

More Azure Data Factory pros

"Stability-wise, I rate the solution a ten out of ten."

"Their automation and workflows are very strong, and you can build the workflows very easily and quickly."

"It's easy to understand, makes flows and is efficient."

"The most valuable features are easy integration, quick tab to develop, quick tab to market, and interactive integration platform."

"It is very easy to use. It takes complex workloads away, and it provides very smooth integration. It has got a lot of out-of-the-box connectors. It has got a lot of out-of-the-box APIs, which makes it really easy to integrate with applications for different use cases, whether it is in finance, HR, or customer operations. It is by far our favorite integration product."

"Workato is low code, intuitive, and easy to use."

"It is easier to use than other technical open-source technologies."

Cons

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"The deployment should be easier."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."

"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."

"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."

"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."

More Azure Data Factory cons

"A limitation is that their cloud presence is only in North America and Europe."

"The management dashboard in the solution is an area with shortcomings that needs improvement."

"I would like to see the dashboarding and reporting processes improved."

"From the deployment point of view, our customers encounter platform downtime where it does not serve the actual request on the systems."

"The only minor drawback would be if there was a UI at the front of it, for apps and for a portal as well, it would make it really easy. It would be really useful if there were more apps capabilities."

"Workato's Extract, transform, and load (ETL) and extract, load, and transform (ELT) are not very strong and could be improved for very complex transformations."

"It is tedious to make a tailor-fit function."

Pricing and Cost Advice

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"I would not say that this product is overly expensive."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"ADF is cheaper compared to AWS."

"The price is fair."

More Azure Data Factory pricing and cost advice

"Workato is an expensive solution."

"On a scale of one to ten, the pricing is around a six. We have a consumption model and the pricing is higher. If you are using any kind of ML-based approach, machine learning, or some advanced analytics, you may have to pay more."

"Speaking about price, I would say that it's market-related. Also, there are costs in addition to the standard license fees since different add-ons depend on what you require."

See which vendors are best for you

Use our free recommendation engine to learn which Data Integration solutions are best for your needs.

See recommendations

824,053 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Educational Organization

42%

Computer Software Company

Financial Services Firm

Manufacturing Company

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?

Workato's Extract, transform, and load (ETL) and extract, load, and transform (ELT) are not very strong and could be improved for very complex transformations. Workato's licensing model is a bit co...

What is your primary use case for Workato?

We use Workato for iPaaS, which is like a middleware enterprise service bus. We use it for transformation, quick data migrations from one platform to another, and building connectivity. It's got ov...

Informatica PowerCenter vs Azure Data Factory

Comparisons

Compared 13% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

Microsoft Azure Logic Apps vs Workato

Compared 25% of the time

SAP Process Orchestration vs Workato

Compared 8% of the time

Oracle Integration Cloud Service vs Workato

Compared 8% of the time

Fivetran vs Workato

Compared 8% of the time

Matillion ETL vs Workato

Compared 5% of the time

More Workato Competitors

Product Reports

Download Azure Data Factory product report

Azure Data Factory

December 2024

Download Workato product report

November 2024

Learn More

Microsoft

Start your 30-day free trial here.

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Named a Leader in iPaaS for Dynamic Integrations by Forrester, Workato is a modern automation and integration platform. With its enterprise-grade capabilities, you can seamlessly integrate and orchestrate workflow automation across cloud and on-premise applications, files and databases without coding.

The Workato team comes from a deep background in building integration products and will continue to expand and change the automation and integration space.

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