We were using Dremio as a data lake query engine tool. We were creating our PDSs and VDSs on top of our S3 buckets, and our data lake and the data-scientist teams were using the data for further processing. We didn't use it for any ETL jobs. We were using it as a data-lake tool.
Database Engineer at a tech services company with 201-500 employees
Beneficial memory competition, good support, and price well
Pros and Cons
- "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."
- "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."
- "Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries."
What is our primary use case?
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I have been using Dremio for approximately two years.
Buyer's Guide
Dremio
June 2026
Learn what your peers think about Dremio. Get advice and tips from experienced pros sharing their opinions. Updated: June 2026.
900,644 professionals have used our research since 2012.
What do I think about the stability of the solution?
Dremio is highly stable.
What do I think about the scalability of the solution?
Dremio is scalable which is a benefit of the solution. You can scale up to the number of instances you want in case you are feeling the load, and in case you feel your query is running low or you are receiving extra traffic.
You can set the configuration while installing and while setting it up in the Dremio. In the configuration file, you can set up a lot of settings, such as what time.
We have approximately 18 people using the solution in my organization.
How are customer service and support?
We have been in touch with the support from Dremio when we had some internal issues. This happened approximately two times. The support is good.
Which solution did I use previously and why did I switch?
This is the first tool in this category that I have used.
How was the initial setup?
Dremio's initial setup took one or two days, one day is sufficient and typical.
What about the implementation team?
There was one DevOps person used for the deployment and maintenance of the solution.
What's my experience with pricing, setup cost, and licensing?
Dremio is less costly competitively to Snowflake or any other tool.
What other advice do I have?
My advice to others is if they are creating a data lake for a customer, Dremio would be useful for a data engineering team. If they're willing to create a data lake and they wanted to use it with the cloud-agnostic tool, then it is a good choice. If this solution meets their requirement they should try it out.
I rate Dremio an eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
Buyer's Guide
Download our free Dremio Report and get advice and tips from experienced pros
sharing their opinions.
Updated: June 2026
Popular Comparisons
Databricks
Teradata
SAP Business Data Cloud
Snowflake
Azure Data Factory
KNIME Business Hub
IBM SPSS Statistics
Alteryx
Dataiku
Amazon SageMaker
OpenText Analytics Database (Vertica)
Altair RapidMiner
Amazon Redshift
Microsoft Azure Synapse Analytics
BigQuery
Buyer's Guide
Download our free Dremio Report and get advice and tips from experienced pros
sharing their opinions.
Quick Links
Learn More: Questions:
- Which are the best end-to-end data science platforms?
- What enterprise data analytics platform has the most powerful data visualization capabilities?
- What Data Science Platform is best suited to a large-scale enterprise?
- When evaluating Data Science Platforms, what aspect do you think is the most important to look for?
- How can ML platforms be used to improve business processes?
- Why is Data Science Platforms important for companies?














