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Dremio Enterprise

Dremio | 24.3.6

Linux/Unix, Amazon Linux 2.0.20240503.0 - 64-bit Amazon Machine Image (AMI)

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External reviews

48 reviews
from G2

External reviews are not included in the AWS star rating for the product.


    Hugh B.

Great product and excellent support

  • November 27, 2020
  • Review verified by G2

What do you like best about the product?
-Convenient web interface for running SQL queries on our data
-Supports a broad range of data source
-Processing for queries is extremely fast when accelerated (rarely over 1 second)
-Python API is fairly easy to use
-Prompt and knowledgeable support team that are always willing to walk us through problems over video call
What do you dislike about the product?
It's hard to say, because most/all of the problems that we've had with Dremio are likely because we're several versions behind due to compatibility problems with some of our legacy infrastructure. eg. missing features that exist in newer versions, or instability problems with reflections that are probably remedied in newer versions. That's on us, though.
What problems is the product solving and how is that benefiting you?
I'm not sure how specific I'm allowed to be so I'm going to be vague here, but we use Dremio as a data platform for an internal analytics tool. It's a convenient way to access a central data source from multiple deployed versions of the tool (for development or demo purposes), so it's been very beneficial for development purposes over our more rudimentary old model.
Recommendations to others considering the product:
For queries over the Python API that return a significant amount of data, make sure you're using ODBC or pyarrow flight rather than the more basic REST API, as it's likely to be a lot faster.


    Insurance

Dremio is helping us democratize data and deliver analytical solutions far quicker than normal.

  • November 26, 2020
  • Review verified by G2

What do you like best about the product?
The product is great but for me its the people. Committed to our success, easy to work with, friendly and professional. From the beginning, we had positive interactions with Dremio and that didn't change after we became a customer. Dremio is a great partner for our company.
What do you dislike about the product?
Its still a relatively new platform so limited community information available.
What problems is the product solving and how is that benefiting you?
We have already proved that we can turn around Data Analytics in a far shorter time with superior performance compared to our legacy technology stack. We would spend hours moving data around via ETL and then some time spent processing cubes or slow queries. Dremio has smoltified this process a lot. As a company we like using SQL and Dremio provides a SQ L access to our data planform which is a hug plus.
Recommendations to others considering the product:
Run a proof of concept, get comfort with it yourself. You will not be disappointed.


    Daniel E.

With Dremio and Power BI combined, a data-driven culture can be established, on all data. (Gemany)

  • November 26, 2020
  • Review verified by G2

What do you like best about the product?
Dremio managed to provide a wide range of existing analysis tools with universal, fast and direct access to the data in a data lake. The time required to provide data and the IT footprint is reduced to a minimum. Intelligent options for caching query results and entire aggregates in memory for specific analysis scenarios makes working with these two tools a pleasure.
What do you dislike about the product?
Currently there is no managed service on the Microsoft Azure platform, which makes deployment difficult. However, Dremio is working hard on this issue.
What problems is the product solving and how is that benefiting you?
The goal with an analysis tool such as Power BI is to discover new insights and to visually present these insights so that other employees can understand them and make better decisions.

Nobody wants to deal with the acquisition or transformation of data. If you have a large amount of data, it is not practical to load this data into Power BI. Dremio enables us to perform analyses directly on the data in the Date Lake without the need for copying.

This turns a Data Lake into a database that can be queried by SQL.
Recommendations to others considering the product:
Have a look at Dremio University.


    Renan P.

Innovative and fast growing solution

  • November 26, 2020
  • Review verified by G2

What do you like best about the product?
Dremio is a powerful solution to connect your applications and BI tools to your data lake. They are very innovative and fast-paced to deliver new features and enhancements. The professional support team is very helpful and tries to understand the customer needs to deliver the best value. The variety of connectors available for the different data sources is really amazing as well the possibility to easily create custom connectors. The fact that the company contributes back to the community developing or open-sourcing tools is really nice.
What do you dislike about the product?
I believe Dremio's weakness is related to CI/CD because there is a couple of libraries, articles and even an open-sourced tool (which is great) to achieve it but it's still very hard and complex to have full automation. As I mentioned before, Dremio is very innovative and fast-paced, so, I believe they will address soon. One missing feature is the native support for Databricks Delta format but as far as I know it's on the roadmap and there is a workaround to be able to work with Delta. Another missing feature is the multi-master solution, it would be very helpful mainly when doing maintenances on the coordinator. Last but not least, it would be good to have the capability to use groups even when not integrated with an AD, LDAP, etc.
What problems is the product solving and how is that benefiting you?
I'm delivering data from our data lake on top of Azure Data Lake Gen2 for both microservices through Rest API and BI tools such as Power BI. We are also using Dremio to accelerate and empower our teams to understand and take insights from data to meet business needs.
Recommendations to others considering the product:
Dremio is a very powerful and fast-growing tool and the support team is very helpful.


    Matthew B.

An effective tool, with great enterprise support.

  • November 25, 2020
  • Review provided by G2

What do you like best about the product?
* Integrates nicely with AWS. supports s3 buckets and aws hosted databases as data sources, as well as being able to use aws glue as a metastore.
* It's fast. Dremio is able to perform complex operations at scale very quickly. Many of our workloads that took tens of hours on our previous data analytics solution, now finish in under a minuet.
* Able to use a wide variety of data sources together. We able to seamlessly combine data from PostgreSQL and parquet files stored on S3 in a single query.
* Easy to connect to from external tools. Using their JDBC, a variety ODBC connectors and REST API we've been able to easily connect to, and use Dremio with a number of external tools on hosted linux or local windows. Jupyter, datagrip, excel, tableau.
* Great support and PS team. Having worked with the support team on issues ranging from inconsequential to major blockers, they have always been very responsive and fast acting.
What do you dislike about the product?
* Isn't currently transactional for data in an object store (s3). At least for an s3 data source you can't define a table then insert data into it. Any data written must be done via a Create table as Select style statement.
* Error clarity. initial errors displayed to users can be quite opaque requiring one to click through to a deeper menu to find the root cause.
What problems is the product solving and how is that benefiting you?
One tool that can query and combine all our data fast despite being stored in different locations with different formats.


    Chemicals

A new way for simplification

  • November 25, 2020
  • Review verified by G2

What do you like best about the product?
Simplification – Single point of data access.
Data Blending – Merge diverse data pools easily
Protection – Enable security and authorization.
Acceleration – Performant reporting and analysis
What do you dislike about the product?
Different roadmap AWS and Azure and not all capabilities you have in AWS are in Azure
What problems is the product solving and how is that benefiting you?
We organized the Lake like a virtual LAB or APP. In a APP we provide for all our user the correct folder structure and all the resources they need to analyze data.
Dremio use the Data lake as a data source . From outside, Dremio looks and behaves like a relational Database


    Ricardo R.

Dremio for Pon Equipment Pon Power, The Netherlands

  • November 25, 2020
  • Review verified by G2

What do you like best about the product?
The ease of use. We all know SQL and that is very flexible. No coding promises great things, but never deliver and complex development is taking a huge amount of time. Everybody understanding SQL should not go to No-Coding for speed, flexibility and (future) migration.
What do you dislike about the product?
The documentation on available functions is lacking. Dremio does not have a built-in Intellisense nor autosave.
What problems is the product solving and how is that benefiting you?
Virtual data warehousing directly on Microsoft CDM.


    Information Technology and Services

Data Virtualization

  • November 24, 2020
  • Review provided by G2

What do you like best about the product?
able to connect data from multiple sources via Native SQL
What do you dislike about the product?
Sharding work on individual executors can be improvise to keep it simple
What problems is the product solving and how is that benefiting you?
- Central Data virtualization
- Democratizing Data
- Technical edge


    Automotive

Self service Data lake acceleration

  • November 23, 2020
  • Review provided by G2

What do you like best about the product?
The confluence of open source technologies to solve one of the most challenging problems of todays Big Data environments. I applaud Dremio and its team in fusing together technologies like Apache Arrow, Vectorized engine, Iceberg etc to bring a unique approach to accelerating the data lake.
The approach to self service through semantic engineering of data has created a new dimension to data analysis and data curation.
What do you dislike about the product?
Dremio's lack of support for database views and external decryption libraries, has created a perception that sometimes overshadows all the advantages it brings.
What problems is the product solving and how is that benefiting you?
Democratizing data by getting data into the hands of the users through self service. Reaping the benefits of Arrow for speed. Leveraging Dremio's support for Iceberg to cater to consumption scenarios that are unpredictable. Leveraging Iceberg's hidden partitioning through Dremio is a key in this area.


    Andrej S.

My Dremio experience as enterprise-wide data platform by big German client

  • November 20, 2020
  • Review verified by G2

What do you like best about the product?
Dremio helps us a lot to manage a high workloads from our reportnig systems and achieve a fast response time for more then 500 management dashboards. Many of our end-users like work with Dremio to avoid additional Data Engineering skills in team. For some of them it was surprisely fast after changing the Reporting from "Import" to "live" connection to move data processing directly to Dremio. But the most demanded feature was Reflections which gave sometimes lightning-fast (less then 1 second) response time without any re-engineering of business logic or reducing the data volumes.
In case of any issues and challenges Dremio was very cooperative on Germany and global level to solve it.
What do you dislike about the product?
As Dremio do not implemented Elastic Engine on Azure we need to maintain Kubernetes cluster to reach out needed ad-hoc scale-out requirements.
What problems is the product solving and how is that benefiting you?
We have a different use cases on the same shared Dremio instance - "classical" Management Reporting, Self Service BI, Data exploration, AI Use Cases and Business Process Automation.
So our worloads ware not equal in time and not always predictable from "big-bang" requests and high-volume scans. But Dremio managed it in smooth way.
Recommendations to others considering the product:
Based on my exprerience Dremio fits for usecases when you:
..have Multi-Cloud stategy and want to avoid "lock-in" effect into one of cloud-vendor solution
..have onPremise Hadoop cluster or ODS store which performance is not enough
..have end users which wants to work directly with data, but have only SQL knowlegde
..want to offload data processing to Dremio from you BI-tools like Tableau or Power BI
..have usecases where time-to-market has a huge value (like a ad-hoc data exploration in Data Science)