Azure Data Factory vs Toad Data Point comparison

Microsoft and Quest Software are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.0, while Quest Software is ranked #52. Microsoft holds a 11.1% mindshare in DI, compared to Quest Software’s 0.5% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Quest Software users who would recommend it.

Azure Data Factory

Read 86 Azure Data Factory reviews

23,087 Views
18,331 Comparison Views

92% willing to recommend

Toad Data Point

Read 2 Toad Data Point reviews

649 Views
554 Comparison Views

100% willing to recommend

Azure Data Factory

Toad Data Point

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and Toad Data Point 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. Toad Data Point Report (Updated: October 2024).

Buyer's Guide

Azure Data Factory vs. Toad Data Point

October 2024

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

Toad Data Point

Ranking in Data Integration

52nd

Average Rating

9.0

Number of Reviews

Ranking in other categories

Data Preparation Tools (7th)

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 Toad Data Point is 0.5%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

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.

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Steven Scarver

VP/Manager, Data Analytics & Intelligence at a financial services firm with 1,001-5,000 employees

Easy to scale, useful auto-formatting, and powerful features

Toad Data could improve by having additional features, such as query prediction. This could help someone who's not the strongest programmer. If the software could help them write queries correctly it would be very helpful, especially for small development teams or teams that lack the input skills necessary to write and program efficiently.

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Quotes from Members

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

Pros

"Powerful but easy-to-use and intuitive."

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

"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."

"The best part of this product is the extraction, transformation, and load."

"The solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."

"The most valuable feature of this solution would be ease of use."

"I like the basic features like the data-based pipelines."

"Azure Data Factory became more user-friendly when data-flows were introduced."

More Azure Data Factory pros

"The Connectivity and Connection Manager supports a broad number of connection types, and it is trivial for end-users to set up their own connections to sources."

"The most valuable features of Toad Data are you could write a parameterized query and it wouldn't error out, it would give you the parameters that you could input. The auto-formatting feature is useful because it was great for keeping your queries neat and understandable. The auto comment, and uncomment toggles that you could do were convenient."

Cons

"The deployment should be easier."

"There's space for improvement in the development process of the data pipelines."

"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."

"Data Factory's monitorability could be better."

"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."

"The speed and performance need to be improved."

"I have not found any real shortcomings within the product."

"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."

More Azure Data Factory cons

"Toad Data could improve by having additional features, such as query prediction. This could help someone who's not the strongest programmer. If the software could help them write queries correctly it would be very helpful, especially for small development teams or teams that lack the input skills necessary to write and program efficiently."

"On the scheduling server, some scheduled reports just sit there and never execute for the first time. After manually executing the first time, they run with no issues."

Pricing and Cost Advice

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"This is a cost-effective solution."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

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

"Pricing appears to be reasonable in my opinion."

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

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

"The solution is cheap."

More Azure Data Factory pricing and cost advice

"The cost of this product is reasonable."

"The price of Toad Data Point was approximately $500 annually."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Financial Services Firm

37%

Healthcare Company

13%

Government

Manufacturing Company

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.

See all answers

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...

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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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Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 14% of the time

Snowflake vs Azure Data Factory

Compared 11% 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

SAS Enterprise Guide vs Toad Data Point

Compared 21% of the time

SSIS vs Toad Data Point

Compared 20% of the time

Alteryx vs Toad Data Point

Compared 19% of the time

Oracle Data Integrator (ODI) vs Toad Data Point

Compared 17% of the time

More Toad Data Point Competitors

Product Reports

Buyer's Guide

Azure Data Factory

November 2024

Download Azure Data Factory product report

Buyer's Guide

Data Integration

November 2024

Download Toad Data Point product report

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Microsoft

Quest Software

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.

Toad Data Point is a cross-platform, self-service, data-integration tool that simplifies data access, preparation and provisioning. It provides nearly limitless data connectivity, desktop data integration, visual query building and workflow automation.

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

Concordia University

Buyer's Guide

Azure Data Factory vs. Toad Data Point

October 2024

Free Report: Azure Data Factory vs. Toad Data Point

Find out what your peers are saying about Azure Data Factory vs. Toad Data Point and other solutions. Updated: October 2024.

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