Azure Data Factory vs Firebolt comparison

Microsoft and Firebolt are both solutions in the Cloud Data Warehouse category. Microsoft is ranked #2 with an average rating of 8.2, while Firebolt is ranked #17. Microsoft holds a 5.3% mindshare in CDW, compared to Firebolt’s 1.7% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Firebolt users who would recommend it.

Azure Data Factory

Read 94 Azure Data Factory reviews

10,752 Views
1,720 Comparison Views

92% willing to recommend

Firebolt

Read 1 Firebolt review

419 Views
369 Comparison Views

100% willing to recommend

Azure Data Factory

Firebolt

Comparison Buyer's Guide

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Executive Summary

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

Find out what your peers are saying about Snowflake Computing, Microsoft, Teradata and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: March 2026).

Buyer's Guide

Cloud Data Warehouse

March 2026

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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

Ranking in Cloud Data Warehouse

2nd

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (3rd)

Firebolt

Ranking in Cloud Data Warehouse

17th

Average Rating

9.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2026, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 5.3%, down from 8.4% compared to the previous year. The mindshare of Firebolt is 1.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	5.3%
Firebolt	1.7%
Other	93.0%

Cloud Data Warehouse

Featured Reviews

KandaswamyMuthukrishnan

Director at a computer software company with 1,001-5,000 employees

Integrates diverse data sources and streamlines ETL processes effectively

Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.

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Iqbal Hossain Raju

Junior Software Engineer at a healthcare company with 10,001+ employees

Can quickly query it to generate quick results

We have used Snowflake before. We support both. Firebolt has better performance, executing queries much quicker than Snowflake. However, Snowflake has more functionality. Depending on the client's needs, we can recommend the best option. Firebolt is a relatively new technology. Snowflake has many functionalities. Firebolt does not support unloading data to S3. There is no built-in way to do this in Firebolt. Alternatively, the data can be retrieved using API calls and loaded to S3 manually. Data can be unloaded to S3 directly using Snowflake. Firebolt significantly improves our performance over Snowflake because it takes less time to execute queries. This is especially important for our company because we use some KPIs that require fast loading times.

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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

"Azure Data Factory is an integration tool, an orchestration service tool; it is for data integration for the cloud."

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

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

"The data is more scalable."

"It is beneficial that the solution is written with Spark as the back end."

"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."

"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."

"The most valuable part of this product is the ease of use, as it is easy to use and rather intuitive, and because it is easy to use, you can do things with it easily, making your work easier and therefore more valuable."

More Azure Data Factory pros

"Firebolt is fast for analytical purposes. For example, we have analytical data in our data warehouse, and Firebolt can quickly query it to generate quick results."

Cons

"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."

"It would be better if it had machine learning capabilities."

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

"Real-time replication is required, and this is not a simple task."

"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."

"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."

"If the user interface was more user friendly and there was better error feedback, it would be helpful."

"As far as customer service and support with Azure Data Factory, we are not always satisfied with the response time."

More Azure Data Factory cons

"Firebolt's engine takes a long time to start because it needs to make engine calls."

Pricing and Cost Advice

"The licensing cost is included in the Synapse."

"The cost is based on the amount of data sets that we are ingesting."

"Data Factory is expensive."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

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

"I would rate Data Factory's pricing nine out of ten."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

"It's not particularly expensive."

More Azure Data Factory pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

10%

Manufacturing Company

Government

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	20
Large Enterprise	57

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

Snowflake vs Azure Data Factory

Compared 5% of the time

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

Compared 5% of the time

Palantir Foundry vs Azure Data Factory

Compared 4% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

Informatica PowerCenter vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Snowflake vs Firebolt

Compared 36% of the time

Snowflake Analytics vs Firebolt

Compared 14% of the time

Yellowbrick Cloud Data Warehouse vs Firebolt

Compared 14% of the time

Databricks vs Firebolt

Compared 13% of the time

Microsoft Azure Synapse Analytics vs Firebolt

Compared 13% of the time

More Firebolt Competitors

Product Reports

Buyer's Guide

Azure Data Factory

April 2026

Download Azure Data Factory product report

Buyer's Guide

Cloud Data Warehouse

March 2026

Download Firebolt product report

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

Firebolt is a cloud-native data warehouse that enables organizations to process massive amounts of data at lightning-fast speeds. This is achieved through its unique architecture that utilizes a cloud-native approach, allowing for elastic scaling and parallel processing.

Firebolt helps organizations with a scalable and cost-effective solution for their data warehousing needs. It eliminates the need for expensive hardware and maintenance costs associated with traditional data warehouses. Firebolt's real-time analytics capabilities also enable businesses to make data-driven decisions quickly, giving them a competitive edge in their respective industries.

Firebolt

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

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Find out what your peers are saying about Snowflake Computing, Microsoft, Teradata and others in Cloud Data Warehouse. Updated: March 2026.

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