Dremio Cloud - Enterprise Edition

I use Dremio  for proof of concept purposes. I haven't used it in a real-time project, however, I explore Dremio  as a data virtualization application in the ecosystem. It is relatively new, possibly a one-year or two-year-old system.

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.

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 does. Starburst has all these capabilities. Dremio has only 15 to 20 connectors, however, Starburst comes with around 50 now.

I have used it for just one month for proof of concept purposes.

I cannot comment on stability as I just worked with it for one month. I haven't worked with large data. When I worked with small data, it was fine at that time.

Internally, if it's on Docker  or Kubernetes , scalability will be built into the system. In the SaaS, I'm unsure as I haven't set it up. I don't know how the integrated SaaS works inside. If it were an enterprise setup like Starburst, I know how it works since I have worked there, using Kubernetes , Docker , and everything. I'm not familiar with Dremio's backend, however, it also works on Kubernetes and similar technologies. Hopefully, scalability will be there for sure.

It was just proof of concept, and we were just exploring the product. We did not deal with technical support 

Neutral

It is a SaaS, so it is straightforward to set up.

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.

We use Dremio  for financial data analytics and as a data lake. We connect Dremio  with Oracle, Docker , MySQL , and utilize it for Power BI. 

Additionally, we use it to process data from MongoDB , although we face occasional challenges with NoSQL integration.

Dremio is very easy to use for building queries. It's easy to connect Dremio to various databases and data sources like Oracle and MySQL . It is also very flexible, providing us with scalability and integration capabilities effortlessly.

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. We face certain issues when connecting Dremio to MongoDB , especially with max values, which seem to be inconsistent in Dremio. 

Additionally, licensing is quite expensive, and we feel the need for more flexible schema capabilities, especially in embedding JSON from MongoDB.

We have been using Dremio for more than two years.

In terms of stability, we experience performance issues occasionally, partly due to our limited experience.

We have not yet scaled Dremio because we are using the community version, and require a license for scaling. We need to learn how to scale up and out more effectively.

We haven't submitted any questions for technical support yet.

Positive

We have worked with various data warehouse solutions, like Oracle, and also used databases on Azure .

The initial setup was straightforward. We run Dremio on an Ubuntu  dedicated server on-premises, and it took us about a day to set up.

We see savings because we don't need more personnel to develop and maintain Dremio. It's cost-effective in terms of manpower.

The licensing is very expensive. We need a license to scale as we are currently using the community version.

We used Oracle and databases on Azure  before using Dremio.

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.