Data Analyst at a insurance company with 501-1,000 employees
Real User
Top 10
Oct 30, 2025
My advice for others looking into using Dremio is to explore the web environment and stay sharp with the ODBC connectors and drivers, as that is very important. I would rate this product a 9.
Senior Consultant - Data Analytics at a comms service provider with 201-500 employees
Real User
Top 5
Oct 21, 2025
I would advise others looking into using Dremio to study the tool beforehand. Dremio has several different offerings, and the best way to get into it is to use the open-source on-premises version to experiment with it. To extract the complete power of the platform, organizations should educate themselves with the complete information and compare it with other solutions since a single solution cannot fit everywhere. Educating the team before adopting a technology is better than just adopting a suggested package. I rate Dremio 8 out of 10.
Regarding features, I'm not sure if they have all the tools like data governance, data quality, and data lineage integrated. If not, they need to build those tools as well to check the data quality and lineage. Data discovery is there. Connectivity-wise, Starburst is way better, however, Dremio might have a better computing path, possibly delivering data faster than Starburst. No direct comparison can be made, so I cannot comment further. Overall, you can rate it as eight out of ten.
Dremio is very flexible and easy to use, making it very suitable for our team. I would recommend Dremio for similar use cases due to its flexibility. On a scale of one to ten, I would rate Dremio at eight.
Sr Manager at a transportation company with 10,001+ employees
Real User
Dec 6, 2023
We are currently evaluating Dremio against other similar products. But at first glance, I would recommend using Dremio. Considering my limited access and experience over these three months, I would rate Dremio around a seven out of ten.
I rate Dermio 10 out of 10. Data lake 2.0 or 3.0 is gradually replacing data warehouses, but it's not quite there yet. We can't get rid of data warehouses, but it's heading in that direction. Dremio is a phenomenal place to start with that mindset shift and architecture shift. Despite the shortcomings, Dremio has made better progress in moving the industry forward than anybody else out there.
I suggest that you give it a try and see for yourself. Dermio is as fast as Presto. For example, ten billion rows can return in less than five seconds. I would rate it a 10 out of 10.
I would advise others not try to use Dremio as an ETL framework from day one. I also recommend do not use reflections, or any other tool which make dremio cluster statefull. The installation for a production environment is complex and I would not recommend this solution for small businesses. I would rate this solution a seven out of ten.
Dremio offers a comprehensive platform for data warehousing and data engineering, integrating seamlessly with data storage systems like Amazon S3 and Azure. Its main features include scalability, query federation, and data reflection.Dremio's core strength lies in its ability to function as a robust data lake query engine and data warehousing solution. It facilitates the creation of complex queries with ease, thanks to its support for Apache Airflow and query federation across endpoints....
My advice for others looking into using Dremio is to explore the web environment and stay sharp with the ODBC connectors and drivers, as that is very important. I would rate this product a 9.
I would advise others looking into using Dremio to study the tool beforehand. Dremio has several different offerings, and the best way to get into it is to use the open-source on-premises version to experiment with it. To extract the complete power of the platform, organizations should educate themselves with the complete information and compare it with other solutions since a single solution cannot fit everywhere. Educating the team before adopting a technology is better than just adopting a suggested package. I rate Dremio 8 out of 10.
Regarding features, I'm not sure if they have all the tools like data governance, data quality, and data lineage integrated. If not, they need to build those tools as well to check the data quality and lineage. Data discovery is there. Connectivity-wise, Starburst is way better, however, Dremio might have a better computing path, possibly delivering data faster than Starburst. No direct comparison can be made, so I cannot comment further. Overall, you can rate it as eight out of ten.
Dremio is very flexible and easy to use, making it very suitable for our team. I would recommend Dremio for similar use cases due to its flexibility. On a scale of one to ten, I would rate Dremio at eight.
Overall, I rate Dremio ten out of ten.
We are currently evaluating Dremio against other similar products. But at first glance, I would recommend using Dremio. Considering my limited access and experience over these three months, I would rate Dremio around a seven out of ten.
I rate Dermio 10 out of 10. Data lake 2.0 or 3.0 is gradually replacing data warehouses, but it's not quite there yet. We can't get rid of data warehouses, but it's heading in that direction. Dremio is a phenomenal place to start with that mindset shift and architecture shift. Despite the shortcomings, Dremio has made better progress in moving the industry forward than anybody else out there.
I suggest that you give it a try and see for yourself. Dermio is as fast as Presto. For example, ten billion rows can return in less than five seconds. I would rate it a 10 out of 10.
I would advise others not try to use Dremio as an ETL framework from day one. I also recommend do not use reflections, or any other tool which make dremio cluster statefull. The installation for a production environment is complex and I would not recommend this solution for small businesses. I would rate this solution a seven out of ten.