We use Dremio for data engineering.
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Self Service for dummies
What do you like best about the product?
Users are in no time familiar with thr usage of Dremio, and administrative tasks in Dremio are super easy.
What do you dislike about the product?
AKS cluster is hard to maintain for us. Needs alignment with IT partner, but hard to find. Looking forward to use a Hosted Dremio solution.
What problems is the product solving and how is that benefiting you?
Connecting multiple sources and easy usage for end users.
A highly stable solution that works like a data warehouse on top of data lakes
What is our primary use case?
How has it helped my organization?
Dremio has resolved my data lineage and data governance problems. The solution has also resolved the data availability for a different range of users, which used to be a problem.
What is most valuable?
Dremio allows querying the files I have on my block storage or object storage. The solution gives me a place where I can play around with the data virtually by creating VDSs or PDSs. Dremio works just like a data warehouse on top of my data lake, which is interesting.
What needs improvement?
Dremio's interface is good, but it has a few limitations. I cannot do a lot of things with ANSI SQL or basic SQL. I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported.
The use case I am working on requires building trees and hierarchical structures. Most of the time, it requires complex nested data structures to be made simpler for end users. It would be good if Dremio could provide a way to create trees just like Oracle does using commands like CONNECT BY and NO CYCLE.
You can use a few languages to simplify complicated JSON and XML. It would be very helpful if Dremio could provide a solution to simplify building trees and building meaningful data from complex data.
What do I think about the stability of the solution?
I rate Dremio ten out of ten for stability.
What do I think about the scalability of the solution?
I rate Dremio ten out of ten for scalability.
How was the initial setup?
I rate Dremio ten out of ten for the ease of its initial setup.
What about the implementation team?
We implemented the solution through an in-house team. Dremio's deployment can be done quickly.
What other advice do I have?
Overall, I rate Dremio ten out of ten.
Offers smooth installation and cloud/on-prem flexibility, but faces integration challenges with Databricks
What is our primary use case?
We have been using it to build one of our frameworks. We primarily use Dremio to create a data framework and a data queue. It's being used in combination with DBT and Databricks.
What is most valuable?
We're still in the exploration phase with Dremio, so it's a bit early to determine its most valuable feature. We're currently deploying it across different departments for various use cases and learning from these internal applications.
What needs improvement?
We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily. We had to set up two different VMs and execute them in a different manner and integrate them.
For how long have I used the solution?
I've been using Dremio for about two to three months now. However, one of our teams has been using it for the past year.
What do I think about the stability of the solution?
From my three months of experience, I haven't noticed any stability issues with Dremio.
What do I think about the scalability of the solution?
In my department, which focuses on data and AI, we have about 538 people. I'm not sure how many are actively using Dremio.
How was the initial setup?
The installation process was quite smooth and didn't present any issues.
We currently have Dremio on the cloud. For proof of concept (POC) purposes, we are using it on-premises.
Which other solutions did I evaluate?
What other advice do I have?
We are currently evaluating Dremio against other similar products. But at first glance, I would recommend using Dremio.
Considering my limited access and experience over these three months, I would rate Dremio around a seven out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
Great Tool to bring many data sources of Big Data together with good performance
What do you like best about the product?
Its easy to configuring many different sources and create virtual data set that do unions across them. I am really happy about performance for data-retrieval
What do you dislike about the product?
There are so many bugs in each versions , So that we have to keep them updated with new release
What problems is the product solving and how is that benefiting you?
Dremio has a feature to make data accessible and usable by a much larger number of users . And reflections feature to make it so easy
Quick database capabilities but sometimes shows minor errors
What is our primary use case?
I can visualize traffic from BI and Tableau on the same page and have my tables and schema on the same page. The data link comprises everything. If I want one structure, I connect it to a big table in the hive and the data team that could read my SQL work on my tables, schemas, table structures and everything all in one place. Dermio is as good as any other Presto engine.
How has it helped my organization?
Everyone uses Dremio in my company; some use it only for the analytics function.
What is most valuable?
The most valuable feature is that you can generate refresh reflections and create your visuals (VDS) because it makes it easier to monitor day-to-day data structure. I can use Dermio to create a visual table without impacting the original by creating an opportunity on my own. I can work on my videos and create reflections, and Dremio allows me to use those reflections. I can know the health of my tables, whether healthy or unhealthy, daily. It is one of the most valuable features of Dremio.
What needs improvement?
One of the areas of improvement is that a table does not break and shows errors. When the 23rd version was released, I had to contact Dermio customer support, and they suggested I update the database to run the table. Sometimes you face common errors like tables running strictly and taking time to run. I think Dermio can improve this part.
An additional feature can be a feature where everyone can see the tables.
For how long have I used the solution?
I have been using Dremio for over 3years now.
What do I think about the stability of the solution?
I would rate the scalability an 9/10 because it shows errors sometimes.
What do I think about the scalability of the solution?
I would rate the scalability a 10/10 based on its recent enhancements.
How are customer service and support?
We had Dremio support service at every point of time we requested it.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Previously, I used Presto regularly.
How was the initial setup?
The initial setup was straightforward.
What about the implementation team?
The deployment was in-house, and only two to three people were involved. We had direct Dermio support communication to support us. We have both cloud and in-house deployment methods.
What was our ROI?
With Dremio its not a loss
What's my experience with pricing, setup cost, and licensing?
Every tool has a value based on its intended purpose and use, and the pricing is worth its value.
Which other solutions did I evaluate?
We tested some other options but Dremio proofs to be better in terms of reliability and scalability, so we submitted our reports and reviews.
What other advice do I have?
I suggest that you give it a try and see for yourself. Dremio is as fast as Presto. For example, ten billion rows can return in less than five seconds.
I would rate it a 10 out of 10.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
User Friendly
What do you like best about the product?
its easy to use and upgrades are simple compared to other products
What do you dislike about the product?
Stability and time it takes for support to resolve issues
What problems is the product solving and how is that benefiting you?
Easy data access
Dremio Review
What do you like best about the product?
I like how easy it is to get the data ready w/o going through the ETL/ELT process.
What do you dislike about the product?
They don't have their own BI too. You have to connect to the 3rd party tools.
What problems is the product solving and how is that benefiting you?
I tried to do a data analytic task.
I am pleased about how easy it is to perform my job.
I am pleased about how easy it is to perform my job.
Revolutionary technology with a natural user interface
What do you like best about the product?
Dremio initially caught my eye because the company grew out of the open-source arrow project, which was already a fantastic project and critical to big data platforms.
Dremio does one thing really well and a couple of other things pretty well:
- To start with, with regards to scalable data access, whether you're accessing terabytes of parquet/files or megabytes of database information, Dremio _just works_. There are very few other solutions that 1) allow you to join different data sources on-demand, 2) do _not_ run 24/7 but spin up clusters when you need them and 3) have a reasonably user-friendly interface. The combination has made Dremio crucial to increasing productivity at my company.
However, Dremio offers even more than the killer feature of easy data access described above:
- Good mechanisms for data governance, including internal lineage graphs between datasets
- Ways to structure computing resources with regards to finetuning query performance -- if you need dashboard datasets to perform more quickly than UI datasets, it's almost a point-and-click operation
- You can expose internal statistics on usage and performance for all queries
- Better and better granularity with regards to managing users
- Most tools only allow users to download a max of 1-10k rows of data. Dremio easily allows 1 million rows and performs on this as well
Dremio has really thought about how companies should manage and expose data and has made sure to provide a design and the technology to make data access, democritization and governance easier.
Dremio does one thing really well and a couple of other things pretty well:
- To start with, with regards to scalable data access, whether you're accessing terabytes of parquet/files or megabytes of database information, Dremio _just works_. There are very few other solutions that 1) allow you to join different data sources on-demand, 2) do _not_ run 24/7 but spin up clusters when you need them and 3) have a reasonably user-friendly interface. The combination has made Dremio crucial to increasing productivity at my company.
However, Dremio offers even more than the killer feature of easy data access described above:
- Good mechanisms for data governance, including internal lineage graphs between datasets
- Ways to structure computing resources with regards to finetuning query performance -- if you need dashboard datasets to perform more quickly than UI datasets, it's almost a point-and-click operation
- You can expose internal statistics on usage and performance for all queries
- Better and better granularity with regards to managing users
- Most tools only allow users to download a max of 1-10k rows of data. Dremio easily allows 1 million rows and performs on this as well
Dremio has really thought about how companies should manage and expose data and has made sure to provide a design and the technology to make data access, democritization and governance easier.
What do you dislike about the product?
Dremio is still a young company and while the product works well, they're still working very hard at improving it.
We have not yet run into a single bug on production, but it was initially noticeable that it's a young product (start 2021).
Fortunately, they are rapidly making new releases and fixing a lot of the little issues so that the product has a good, professional level of quality.
We have not yet run into a single bug on production, but it was initially noticeable that it's a young product (start 2021).
Fortunately, they are rapidly making new releases and fixing a lot of the little issues so that the product has a good, professional level of quality.
What problems is the product solving and how is that benefiting you?
As I mentioned above, Dremio solves data access in a performant, easy way -- and much easier, faster and in a smarter way than any other tool that I've yet to come across in 2021.
Recommendations to others considering the product:
Dremio is more expensive for smaller organizations -- even though we are smaller and it is thus more expensive for us, it's been able to solve problems that cheaper solutions were not capable of, in particular easy, scalable, manageable performant data access.
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.
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.
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