* Integrates nicely with AWS. supports s3 buckets and aws hosted databases as data sources, as well as being able to use aws glue as a metastore.

* It's fast. Dremio is able to perform complex operations at scale very quickly. Many of our workloads that took tens of hours on our previous data analytics solution, now finish in under a minuet.

* Able to use a wide variety of data sources together. We able to seamlessly combine data from PostgreSQL and parquet files stored on S3 in a single query.

* Easy to connect to from external tools. Using their JDBC, a variety ODBC connectors and REST API we've been able to easily connect to, and use Dremio with a number of external tools on hosted linux or local windows. Jupyter, datagrip, excel, tableau.

* Great support and PS team. Having worked with the support team on issues ranging from inconsequential to major blockers, they have always been very responsive and fast acting. Review collected by and hosted on G2.com.

* Isn't currently transactional for data in an object store (s3). At least for an s3 data source you can't define a table then insert data into it. Any data written must be done via a Create table as Select style statement.

* Error clarity. initial errors displayed to users can be quite opaque requiring one to click through to a deeper menu to find the root cause. Review collected by and hosted on G2.com.

The product is great but for me its the people. Committed to our success, easy to work with, friendly and professional. From the beginning, we had positive interactions with Dremio and that didn't change after we became a customer. Dremio is a great partner for our company. Review collected by and hosted on G2.com.

Its still a relatively new platform so limited community information available. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Simplicity of use and power of window functions. Review collected by and hosted on G2.com.

Lack of Undo and Redoo buttons in web user interface. Review collected by and hosted on G2.com.

SQL API to all the data on the data lake. Review collected by and hosted on G2.com.

I needed a DevOps person to take care of deployment. Review collected by and hosted on G2.com.

The ease of use. We all know SQL and that is very flexible. No coding promises great things, but never deliver and complex development is taking a huge amount of time. Everybody understanding SQL should not go to No-Coding for speed, flexibility and (future) migration. Review collected by and hosted on G2.com.

The documentation on available functions is lacking. Dremio does not have a built-in Intellisense nor autosave. Review collected by and hosted on G2.com.

Dremio is simple to use, scales well and have great customer support Review collected by and hosted on G2.com.

A larger community on the internet will help in resolving issues faster. Hopefully it will happen soon as more customers start using Dremio Review collected by and hosted on G2.com.

Easy to scale and excellent performance. Review collected by and hosted on G2.com.

Reflections have to be manually managed. Review collected by and hosted on G2.com.

The confluence of open source technologies to solve one of the most challenging problems of todays Big Data environments. I applaud Dremio and its team in fusing together technologies like Apache Arrow, Vectorized engine, Iceberg etc to bring a unique approach to accelerating the data lake.

The approach to self service through semantic engineering of data has created a new dimension to data analysis and data curation. Review collected by and hosted on G2.com.

Dremio's lack of support for database views and external decryption libraries, has created a perception that sometimes overshadows all the advantages it brings. Review collected by and hosted on G2.com.

Simplification – Single point of data access.

Data Blending – Merge diverse data pools easily

Protection – Enable security and authorization.

Acceleration – Performant reporting and analysis Review collected by and hosted on G2.com.

Different roadmap AWS and Azure and not all capabilities you have in AWS are in Azure Review collected by and hosted on G2.com.