64 Dremio Reviews
Overall Review Sentiment for Dremio
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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 Review collected by and hosted on G2.com.
There are so many bugs in each versions , So that we have to keep them updated with new release Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
- 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. Review collected by and hosted on G2.com.
Lack of database connectors (a.e. BigQuery, Cassandra).
UI will be improved in the next version. Review collected by and hosted on G2.com.
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! Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
The need for a strong cluster that companies in an early data transformation stage have not necessarily. Review collected by and hosted on G2.com.
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! Review collected by and hosted on G2.com.
Dremio isn't an industry standard (yet), so help on the official forums or rest of the internet can be quite limited. Review collected by and hosted on G2.com.
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! Review collected by and hosted on G2.com.
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. Review collected by and hosted on G2.com.
