Dremio Enterprise
DremioExternal reviews
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Accelerate your data transformation by freeing up access to your datalake
What do you like best about the product?
The capacity to create specific data marts for each department that are sourced from a common database for all the company.
The reflection feature is also remarkable as it enables us to save storage and reduce our daily data transformation jobs.
The reflection feature is also remarkable as it enables us to save storage and reduce our daily data transformation jobs.
What do you dislike about the product?
The need for a strong cluster that companies in an early data transformation stage have not necessarily.
What problems is the product solving and how is that benefiting you?
We are putting in place self BI inside the company.
We are then aiming to launch Advanced Analytics use cases (Churn, appetence scores, risk ratings, etc.)
Finally, we aim to feed our CRM with a customer omnichannel view + insights from the Advanced Analytics Use cases.
Two months after putting in place Dremio, our Risk Department has autonomously created its own Data Mart and used it in Tableau Software to create a dozen reportings from board level to branch one.
We are then aiming to launch Advanced Analytics use cases (Churn, appetence scores, risk ratings, etc.)
Finally, we aim to feed our CRM with a customer omnichannel view + insights from the Advanced Analytics Use cases.
Two months after putting in place Dremio, our Risk Department has autonomously created its own Data Mart and used it in Tableau Software to create a dozen reportings from board level to branch one.
Great tool to simplify and accelerate big data queries across multiple heterogeneous data sources
What do you like best about the product?
Easy to scale and excellent performance.
What do you dislike about the product?
Reflections have to be manually managed.
What problems is the product solving and how is that benefiting you?
Speed up queries across multiple data sources.
Next Generation SQL Engine
What do you like best about the product?
Dremio offers amazing SQL performance for our Cloud Data Lake
The UI is intuitive and offers some nice data preparation capabilities
Dremio's data strategy aligns with ours
Arrow Flight will offer a step-change in capability
The UI is intuitive and offers some nice data preparation capabilities
Dremio's data strategy aligns with ours
Arrow Flight will offer a step-change in capability
What do you dislike about the product?
Dremio's user documentation is lagging behind their capabilities
Dremio has some hard limits on the numbers of columns and fields that need to be raised to cover all use cases
Dremio has some hard limits on the numbers of columns and fields that need to be raised to cover all use cases
What problems is the product solving and how is that benefiting you?
Dremio is the foundation layer in our Analytics Stack, providing direct SQL access to PB of data and connectivity to advanced Analytic, ML and data visualisation tools. It's supporting our strategy to reduce/ eliminate the need for specialised data warehouse technology
Accelerating Client Resiliency through enabling data driven insights
What do you like best about the product?
Intuitive, effective and transformative. Dremio enables us to provide quicker time to insights for our clients and internal uses. The tool is very user friendly. Their support team is awesome and always super helpful as well. Personal experience through the Dremio Support and Sales teams and open to feedback. The tool supports alot of downstream connections and usage through its API and JDBC/ODBC connection which we use to visualize and present insights to our clients and customers.
What do you dislike about the product?
Limited Data Source Connections is something we constant run into issues with. RBAC would be a great feature as well since single sign on through AAD doesnt keep credentials just gives access to the platform. Also difficult to see the logs without putting in some extra effort to find them. Dremio is still developing and we understand that some of these dislikes are currently being resolved through the course of the products development.
What problems is the product solving and how is that benefiting you?
We are helping organizations be more resilient through black swan events by driving and guiding their data insights and actions based on data. We have realized quicker time to pull data together and perform analysis to drive decisions. This has saved clients money and time on a regular basis! We are seeing great interest in our clients to solve issues around siloed data, duplicate data, non democrotized reporting data and insights. The need to standardize the approach to data and govern and access in a consistent manner.
Data Lake Adoption
What do you like best about the product?
Enabling interactive speed queries on Hadoop
What do you dislike about the product?
Can be misused as a mainstream ELT tool.
What problems is the product solving and how is that benefiting you?
Making Hadoop as the mainstream data platform for all consumers. This tool has really flattened the Change management curve for the BI community in adopting the Data Lake on Hadoop
A virtual integration environment to allow data analyzing on a higher and faster level
What do you like best about the product?
Easy to use, SQL based, No data movement, optimizing and integrate queries and/or the use of reflections for a high analyzing performance
What do you dislike about the product?
At this moment no actual issues, maybe a missing data dictionary
What problems is the product solving and how is that benefiting you?
No data movement, self service analytics
Great product and excellent support
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
-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.
A new way for simplification
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
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
Dremio use the Data lake as a data source . From outside, Dremio looks and behaves like a relational Database
Dremio for Pon Equipment Pon Power, The Netherlands
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.
My Dremio experience as enterprise-wide data platform by big German client
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.
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.
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)
..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)
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