Dremio AWS - BYOL
Dremio | 25.0.4Linux/Unix, Amazon Linux 2.0.20240610.1 - 64-bit Amazon Machine Image (AMI)
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Handy engine to bring many sources of Big Data together with good performance
What do you like best about the product?
I really like the ease of configuring many different sources and create views that do unions across them. I'm also a big fan of Flight's performance for data-retrieval!
What do you dislike about the product?
Dremio isn't an industry standard (yet), so help on the official forums or rest of the internet can be quite limited.
What problems is the product solving and how is that benefiting you?
We're aiming to offer a single view, that exposes near-live intraday data (in low-latency storage solutions) as well as far-back history (in high-bandwidth Big Data stores). We try to make it as easy, transparent and performant as possible for users to access any data we store internally.
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Dremio as a next-generation data lake engine
What do you like best about the product?
- Dremio allows business users to access data easily on multiple platform (HDFS, Oracle RDBMS, SQL Server, Json, etc.)
- Standardized semantic layer: Eliminate the need for copying and moving data—no more cubes, aggregation tables or extracts—and recurring instances of data drift.
- Accelerate dashboards and reports: Integrate BI tools such as Tableau, PowerBI directly with Dremio and accelerate dashboard/reporting queries
- Accelerate ad-hoc queries: Driving lightning-fast queries directly on your data lake storage. Dremio’s combination of technologies—including an Apache Arrow-based engine.
- Standardized semantic layer: Eliminate the need for copying and moving data—no more cubes, aggregation tables or extracts—and recurring instances of data drift.
- Accelerate dashboards and reports: Integrate BI tools such as Tableau, PowerBI directly with Dremio and accelerate dashboard/reporting queries
- Accelerate ad-hoc queries: Driving lightning-fast queries directly on your data lake storage. Dremio’s combination of technologies—including an Apache Arrow-based engine.
What do you dislike about the product?
Lack of database connectors (a.e. BigQuery, Cassandra).
UI will be improved in the next version.
UI will be improved in the next version.
What problems is the product solving and how is that benefiting you?
We are putting in place a Data Virtualization Layer (Dremio) inside the company.
The business users are able to access and connect the data of multiple source systems with Dremio.
We are then aiming to launch Advanced Analytics use cases.
The business users are able to access and connect the data of multiple source systems with Dremio.
We are then aiming to launch Advanced Analytics use cases.
Had a great experience building our Data Virtualisation layer with Dremio on top of our Data Lake.
What do you like best about the product?
Lightning-fast query speeds, ability to easily work with data lakes
What do you dislike about the product?
Intermittent issues, needs to be tested on a wider range of datasets
What problems is the product solving and how is that benefiting you?
Moving from Data Warehouse to Lakehoue
Recommendations to others considering the product:
Dremio is most suitable for organizations with huge volumes of data (in 100s of GBs). That is also when you will be able to see the value of Dremio vs a traditional Data Warehouse
Flexibility in data management
What do you like best about the product?
-Dremio allows business analysts to access data easily on any platform (HDFS, Oracle RDBMS, EnterpriseDB, SQL Server, etc.)
-Cross-platform queries a huge advantage
-Helps to get rid of unneccesarry ETL jobs
-Brings data lake close to the business, it has helped a lot in the demistification of big data technologies
-There are continuous improvements which makes Dremio better and better
-Cross-platform queries a huge advantage
-Helps to get rid of unneccesarry ETL jobs
-Brings data lake close to the business, it has helped a lot in the demistification of big data technologies
-There are continuous improvements which makes Dremio better and better
What do you dislike about the product?
-Lack of NoSQL database connectors (HBase, BigQuery, Cassandra)
-The UI could be more user friendly
-The UI could be more user friendly
What problems is the product solving and how is that benefiting you?
Our objective was to consolidate and streamline data management across multiple data domains and provide fast access to customer data from diverse sources. With Dremio we have achieved it pretty fast.
Dremio is really cool!
What do you like best about the product?
With a tiny engineering team (1) we were able to get Dremio up and running in AWS for our org to start using. It is extremely easy to bring silos of data from all over the organization held in various formats and make them available in our platform.
Once in the platform, it provides a non-threatening interface to allow both analysts and non-analysts the ability to search, find and query the data for their use cases. Dremio has done a wonderful job!
Once in the platform, it provides a non-threatening interface to allow both analysts and non-analysts the ability to search, find and query the data for their use cases. Dremio has done a wonderful job!
What do you dislike about the product?
Dremio definitely puts the "democracy" in "data democratization", but I wish there were more tools to allow a little more control of what data sources are made public on the platform. An organization wouldn't want to be too strict over who can do things in this powerful platform, but being too open could result in data confusion.
Data governance tools to help make sure appropriate documentation or tagging are provided or possibily a request/approval workflow before something is made public to everyone would be really nice.
Data governance tools to help make sure appropriate documentation or tagging are provided or possibily a request/approval workflow before something is made public to everyone would be really nice.
What problems is the product solving and how is that benefiting you?
The biggest problem we are solving is around the data silos in our organization. Dremio allows us to make data accessible and usable by a much larger population.
Recommendations to others considering the product:
If you are looking for a centralized data platform for your org, you should include Dremio in your evaluations. Definitely worth your time learning more about.
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
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.
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