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

Azure Data Factory vs Dremio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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
6.9
Number of Reviews
92
Ranking in other categories
Data Integration (1st)
Dremio
Ranking in Cloud Data Warehouse
6th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
8
Ranking in other categories
Data Science Platforms (10th)
 

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of Azure Data Factory is 6.8%, down from 9.4% compared to the previous year. The mindshare of Dremio is 8.9%, up from 8.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Azure Data Factory6.8%
Dremio8.9%
Other84.3%
Cloud Data Warehouse
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
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.
KamleshPant - PeerSpot reviewer
Solution offers quick data connection with an edge in computation
It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS. It is a similar experience between the based application and cloud-based application. You just get the source, connect the data, get visualization, get connected, and do whatever you want. They say data reflection is one way where they do the caching and all that. Starburst also does the caching. In Starburst, you have a data product. Here, the data product comes from a reflection perspective. The y are working on a columnar memory map, columnar computation. That will have some edge in computation.

Quotes from Members

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

Pros

"I am one hundred percent happy with the stability."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"The most important feature is that it can help you do the multi-threading concepts."
"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."
"The solution has a good interface and the integration with GitHub is very useful."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"The scalability of the product is impressive."
"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Dremio allows querying the files I have on my block storage or object storage."
"Overall, you can rate it as eight out of ten."
"We primarily use Dremio to create a data framework and a data queue."
 

Cons

"The initial setup is not very straightforward."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."
"The number of standard adaptors could be extended further."
"Some known bugs and issues with Azure Data Factory could be rectified."
"When the record fails, it's tough to identify and log."
"They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today."
"There are performance issues at times due to our limited experience with Dremio, and the fact that we are running it on single nodes using a community version."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"They need to have multiple connectors."
 

Pricing and Cost Advice

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"The licensing cost is included in the Synapse."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"Data Factory is affordable."
"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."
"I don't see a cost; it appears to be included in general support."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"Dremio is less costly competitively to Snowflake or any other tool."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
869,566 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
Financial Services Firm
29%
Computer Software Company
9%
Manufacturing Company
7%
Healthcare Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise3
Large Enterprise4
 

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 Dremio?
Dremio allows querying the files I have on my block storage or object storage.
What is your experience regarding pricing and costs for Dremio?
The licensing is very expensive. We need a license to scale as we are currently using the community version.
What needs improvement with Dremio?
They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today. They don't have Salesforce connectivity. However, Starburst do...
 

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
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about Azure Data Factory vs. Dremio and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.