Dremio AWS - Community Edition
Dremio | 24.3.3Linux/Unix, Amazon Linux 2.0.20240131.0 - 64-bit Amazon Machine Image (AMI)
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Efficient and User Friendly SQL layer on top of open file format
What do you like best about the product?
Fast and user-friendly query engine on top of open standard parquet files without the hassle of data loading process to a proprietary vendor format. We used to have to load our Spark-processed data to AWS Redshift in order to get decent performance from our datasets and then we use AWS Athena to avoid the hassle of secondary data loading, but encounter issues with performance SLA with Athena when traffic increases. With Dremio, we have the best of both worlds where the get the comparable performance of Redshift for most of our queries without the hassle of data loading and the reliable performance SLA. The nice user-friendly GUI that our users can use for their SQL queries is definitely a big plus for our end-user tooling and onboarding.
Aside from these, their AWS Edition has the great Elastic Engine feature that helps you save cost by turning off the engine when not in use and automatically turn it on when a query comes in. This has helped us keep our costs under control.
Aside from these, their AWS Edition has the great Elastic Engine feature that helps you save cost by turning off the engine when not in use and automatically turn it on when a query comes in. This has helped us keep our costs under control.
What do you dislike about the product?
The support for larger datasets with a large number of splits is an issue currently, but the move to use Apache Iceberg is in the works to overcome this limitation.
What problems is the product solving and how is that benefiting you?
Data virtualization and democratization. As most of our users come from SQL background, Dremio is the perfect solution for these users to something that they are already familiar with. The web GUI has streamlined our data quality analysts' job as they can simply perform their initial data exploration from the GUI.
Recommendations to others considering the product:
If you dislike proprietary vendor format and the hassle of the data loading process, try this out. Try their community AWS Edition which has most of the features that you would need.
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It is really a very fast analytic engine compare to other competitors
What do you like best about the product?
Setup and query execution also awse features, reflections
What do you dislike about the product?
Sometimes machines crashes due to aws upgrades
What problems is the product solving and how is that benefiting you?
Query execution is too fast around 7 times faster than athena
Strategic Partner
What do you like best about the product?
Upon selecting Dremio as a targeted consumption solution for our enterprise data footprint, Dremio immediately came along side our organization with their architects, designers, and client partners to understand the pending impediments. Through an arduous internal process, Dremio was able to quickly modify their platform to meet our security and compliance needs for a rapid deployment ultimately meeting out timelines.
What do you dislike about the product?
So far so good, they have been nothing but great partners.
What problems is the product solving and how is that benefiting you?
In our large scale data environment we are looking to leverage strategic tools like Dremio in order to limit the transformation and ingestion activities that currently take place within our enterprise lakes. Dremio will ultimately reduce our ETL developments allowing us to deliver insights and results to our business partners significantly faster.
Solid platform and excellent support.
What do you like best about the product?
What I like best about Dremio is the open source foundation and commitments to the open source community. This is most notable in the various database connector where we have the freedom to create our own or modify as needed.
What do you dislike about the product?
The limitations in connection to legacy DBs and there are limitation in maintaining sessions and passing things like "Alter" commands to source databases. This can increase development and adoption timelines.
What problems is the product solving and how is that benefiting you?
Dremio is positioned to solve for virtualization and federation to legacy databases as well as their core product of enabling SQL interfaces on data lakes.
Fast and Open Data Lake Engine
What do you like best about the product?
Amazing performance with Apache Arrow at its core with new enhancements actively developed with the open source community such as Gandiva for optimized execution and Flight for optimized data transfer. Project Nessie is also being worked on in the open source community to bring git-like version history to datasets.
What do you dislike about the product?
There can be better support for large datasets in the TB/PB range in terms of dataset management, with something like Iceberg support, which is in the works.
What problems is the product solving and how is that benefiting you?
Building an open file-based data warehouse that can scale to speed up existing RDBMS-based workloads and allow new and more advanced use cases to be developed on top of data from various sources.
Next Gen tool to accelerate Datalake & AI
What do you like best about the product?
Dremio is a very simple tool to deploy and with OSS technology. We benched many solutions in order to find an performing tool that can accelerate Analytics & ML on-premise
What do you dislike about the product?
Need better integration with Analytics tools like spark (ex: native connectors...)
What problems is the product solving and how is that benefiting you?
- Accelerate Analytics
- Avoid duplicated datasources shared between Analytics & ML
- Self-service DataHub for business
- Avoid duplicated datasources shared between Analytics & ML
- Self-service DataHub for business
Recommendations to others considering the product:
Give a try to Dremio ! you will be surprised.
Excellent Data Tool
What do you like best about the product?
Ability and ease to view data, especially parquet files and their data types.
What do you dislike about the product?
There is not much to dislike, the UI is great too and documentation is thorough.
What problems is the product solving and how is that benefiting you?
Ability to consolidate multiple data sources of big data. Ability to aggregate across DBs and make data available from a single endpoint.
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