Dremio Enterprise
Dremio | 25.0.0Linux/Unix, Amazon Linux 2.0.20240306.2 - 64-bit Amazon Machine Image (AMI)
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A great tool to unlock your data
What do you like best about the product?
Dremio is simple to use, scales well and have great customer support
What do you dislike about the product?
A larger community on the internet will help in resolving issues faster. Hopefully it will happen soon as more customers start using Dremio
What problems is the product solving and how is that benefiting you?
Unlocking the data in the data lake and the data warehouse
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Great software for data virtualization and Data Lake engine
What do you like best about the product?
- Simple UI
- Low entry threshold for enduser (SQL is enough)
- Data Virtualization - one point to access lots of heterogeneous sources
- Materialization features
- Makes our ad hoc and self-service very fast.
- Low entry threshold for enduser (SQL is enough)
- Data Virtualization - one point to access lots of heterogeneous sources
- Materialization features
- Makes our ad hoc and self-service very fast.
What do you dislike about the product?
- No scheduling for materializations yet.
- Some work is needed regarding logs/error descriptions - sometimes they're not very understandable.
- Some work is needed regarding logs/error descriptions - sometimes they're not very understandable.
What problems is the product solving and how is that benefiting you?
- Ad hoc analytics
- Data preparation for Data Science/AI/ML purposes
- Self-service reporting
- Centralizing access to various sources.
- Data preparation for Data Science/AI/ML purposes
- Self-service reporting
- Centralizing access to various sources.
Recommendations to others considering the product:
Wisely consider your cluster size and your semantic layers structure
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.
Enabling fast and easy access to historically scattered enterprise data (Germany)
What do you like best about the product?
With Dremio we provided a single point of access to all available data in multiple op-cos and departments. Supporting a broad range of data storage technologies, Dremio is a perfect fit to provide a holistic combined view of all data available.
On the data-consuming side, Dremio also supports most of the various technologies used in the enterprise context. Ranging from Tableau and PowerBi to ODBC for Excel and in-house custom build systems.
The ability to describe standardized business data views in virtual data sets allows a unified data model. This is possible without the need to re-organize and move data physically.
On the data-consuming side, Dremio also supports most of the various technologies used in the enterprise context. Ranging from Tableau and PowerBi to ODBC for Excel and in-house custom build systems.
The ability to describe standardized business data views in virtual data sets allows a unified data model. This is possible without the need to re-organize and move data physically.
What do you dislike about the product?
For us there could be support for even more data formats.
What problems is the product solving and how is that benefiting you?
We've seen much more agility when creating data models for BI, analytics and data-consuming applications.
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.
Made us rethink our whole architecture!
What do you like best about the product?
The ease of which it allows you to quickly explore new data sets, is impressive. I am always in awe at how quickly we can consume huge data sets (folders full of CSV or Parquet files) and structure them to work as a single data table. This process would have typically taken an IT resource to create/apply a script to manipulate/load the data into a database or single file, and we have our "business" users with no IT experience doing it right away. They still rely on IT to write queries against it for them, but they can explore the data right away. With a little training, even our "business" users are writing SQL to explore the data.
We have a large-scale project to allow our entire organization access to the data they need to do their jobs. We had a large-scale ETL process that transforms that data into a data model and combines data generated inside our firm to data provided from our vendors. Adding Dremio into our environment meant that we no longer have to model the data provided by our vendors. We can spend more time modeling our internal data and running additional data quality checks instead of constantly adjusting our data model when we want to onboard new data from external vendors.
With personal spaces, our end users can upload a simple Excel document and join that to the data we have made available in our platform with no assistance from IT. And with the latest tools provided by the Dremio Professional Services, we now have the reports to show us what users are using what data sets! This allows us to constantly monitor our environment for bottlenecks and stale or unused data sets. This is a massive win for us!
We have a large-scale project to allow our entire organization access to the data they need to do their jobs. We had a large-scale ETL process that transforms that data into a data model and combines data generated inside our firm to data provided from our vendors. Adding Dremio into our environment meant that we no longer have to model the data provided by our vendors. We can spend more time modeling our internal data and running additional data quality checks instead of constantly adjusting our data model when we want to onboard new data from external vendors.
With personal spaces, our end users can upload a simple Excel document and join that to the data we have made available in our platform with no assistance from IT. And with the latest tools provided by the Dremio Professional Services, we now have the reports to show us what users are using what data sets! This allows us to constantly monitor our environment for bottlenecks and stale or unused data sets. This is a massive win for us!
What do you dislike about the product?
While Dremio has been a huge asset to the firm, there are several things that could be improved and there are some scenarios we have seen that it is not the appropriate tool for. We have an environment that has multiple storage accounts in the cloud and several databases that we connect to. We have had several performance issues when we combine data in our data lake to the databases. It turns processes into a single threaded query and essentially locks up or blocks all access to both the dremio environment and the database (Synapse in this case). Since implementing Dremio they have added Delta Lake support and we have turned to this to solve that issue. Since implementing Delta Lake instead of Synapse, we have essentially eliminated this issue.
As with any tool, there is a learning curve to the interface, the interface is rich and has a lot of features but lacks some usability aspects. We have provided feedback to Dremio on this and they have been attentive to these requests so I have confidence this will get better. Going from a typical SQL IDE like Management Studio is a bit of an adjustment, but you get used to it.
We user Power BI and to date, Dremio is not a first level provider for Power BI. You can connect and consume data from Dremio, but I cannot get information about what user is connecting, etc. I am waiting for MS to make them a first party provider.
As with any tool, there is a learning curve to the interface, the interface is rich and has a lot of features but lacks some usability aspects. We have provided feedback to Dremio on this and they have been attentive to these requests so I have confidence this will get better. Going from a typical SQL IDE like Management Studio is a bit of an adjustment, but you get used to it.
We user Power BI and to date, Dremio is not a first level provider for Power BI. You can connect and consume data from Dremio, but I cannot get information about what user is connecting, etc. I am waiting for MS to make them a first party provider.
What problems is the product solving and how is that benefiting you?
We were trying to solve a data virtualization issue. We wanted to disconnect the data we provide to our end users from the physical data sources we get the data. Using the best practices of Dremio, we have been able to accomplish this and have already benefited from this. We were able to adjust from providing data from a Synapse instance to Delta Lake with zero impact to our end users and did not have change any of our queries.
Another side benefit of using Dremio is the time to market of our external data. We are able to quickly onboard sample data from the vendor and allow end users to explore this to determine if this is something they wish to pay for. We can then automate the feed of that data very quickly and make it immediately available.
Another side benefit of using Dremio is the time to market of our external data. We are able to quickly onboard sample data from the vendor and allow end users to explore this to determine if this is something they wish to pay for. We can then automate the feed of that data very quickly and make it immediately available.
Turn on the lights on the data lake
What do you like best about the product?
The best thing about Dremio is that it's very easy to use from the start. And then the more you work with it, the more you discover, you see that it's also really powerful as a query engine, as a data catalog, and as a query accelerator.
Beyond the software itself, the company is very cool. The people are very smart, knowledgeable, and always helpful.
Beyond the software itself, the company is very cool. The people are very smart, knowledgeable, and always helpful.
What do you dislike about the product?
I think there's room for improvement in surfacing error messages to users.
What problems is the product solving and how is that benefiting you?
We are making it easy to analyze the data from our data lake and quickly surface data in some other databases.
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
Senior Data Engineer
What do you like best about the product?
Simplicity of use and power of window functions.
What do you dislike about the product?
Lack of Undo and Redoo buttons in web user interface.
What problems is the product solving and how is that benefiting you?
Dremio is used to query large amount of data retrieved from production lines.
Simplify Data Engineering.
What do you like best about the product?
SQL API to all the data on the data lake.
What do you dislike about the product?
I needed a DevOps person to take care of deployment.
What problems is the product solving and how is that benefiting you?
It is enabling data access to data scientists.
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