Azure Data Factory vs Infobright DB comparison

Microsoft and Ignite Technologies are both solutions in the Cloud Data Warehouse category. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 80% of Ignite Technologies users who would recommend it.

Azure Data Factory

Read 90 Azure Data Factory reviews

4,155 Views
3,276 Comparison Views

92% willing to recommend

Infobright DB

Read 10 Infobright DB reviews

172 Views
110 Comparison Views

80% willing to recommend

Azure Data Factory

Infobright DB

Comparison Buyer's Guide

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Executive Summary

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

Find out in this report how the two Cloud Data Warehouse 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. Infobright DB Report (Updated: April 2025).

Buyer's Guide

Azure Data Factory vs. Infobright DB

April 2025

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Review summaries and opinions

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

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)

Infobright DB

Average Rating

7.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Relational Databases Tools (37th), Data Warehouse (27th)

Featured Reviews

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

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.

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Steve Dodge

Senior System Architect - Resiliency Engineering at AT&T

If you need a real big data solution, look for a distributed solution that actually has a proven track record.

This version of Infobright has zero support for distributed scalability. The internal smart grid employed for each table has a major flaw in that the data size cannot be expunged until 2GB of data is reached at the column-level. This is a major flaw, making usage in a big-data scenario impossible. This means that you can delete as many records from a database table as you want. However, unless the 2GB aggregate size threshold was reached for some of the columns in the table, no reduction in disk space usage will occur. Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk. I spent countless hours trying to find some workaround for this. I have nightmares of my e-mail inbox full of unsolvable questions about data size reduction from our field engineers.

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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

"The solution has a good interface and the integration with GitHub is very useful."

"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."

"The data is more scalable."

"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."

"It is a complete ETL Solution."

"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."

"The data copy template is a valuable feature."

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

More Azure Data Factory pros

"It has very amazing smart grid query feature for very fast aggregate queries across millions of rows"

Cons

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."

"The one element of the solution that we have used and could be improved is the user interface."

"There is a problem with the integration with third-party solutions, particularly with SAP."

"The product integration with advanced coding options could cater to users needing more customization."

"I have encountered a problem with the integration with third-party solutions, particularly with SAP."

"The support and the documentation can be improved."

"There are limitations when processing more than one GD file."

"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."

More Azure Data Factory cons

"Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk."

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."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."

"Data Factory is 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."

"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."

"Product is priced at the market standard."

"Pricing appears to be reasonable in my opinion."

More Azure Data Factory pricing and cost advice

"Our pricing was based on server instances and it was actually very cheap compared to Oracle. I guess you get what you pay for."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

No data available

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.

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 11% of the time

Snowflake vs Azure Data Factory

Compared 9% of the time

Alteryx Designer vs Azure Data Factory

Compared 6% of the time

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

Compared 6% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 5% of the time

More Azure Data Factory Competitors

No data available

Product Reports

Buyer's Guide

Azure Data Factory

April 2025

Download Azure Data Factory product report

Buyer's Guide

Infobright DB

April 2025

Download Infobright DB product report

Also Known As

No data available

Infobright

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.

Microsoft

Infobright's high performance analytic database is designed for analyzing large volumes of machine-generated data

Ignite Technologies

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

REZ-1, SonicWALL, IntegriChain, Fuseforward International Inc., Polystar, Live Rail, Mavenir Systems, JDSU Partners, Bango

Buyer's Guide

Azure Data Factory vs. Infobright DB

April 2025

Free Report: Azure Data Factory vs. Infobright DB

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