Dremio AWS - BYOL

What do you like best about the product?

I love the platform’s ability to connect to a wide array of data sources, including relational databases (PostgreSQL, MySQL, Oracle, MS SQL), NoSQL systems (MongoDB, Elasticsearch), and cloud or file-based storage like S3 and HDFS, without requiring complex ETL pipelines.

This approach simplifies data integration and reduces engineering overhead.

The SQL query engine is highly performant, delivering sub-second response times even on large datasets, and supports live data visualization and dynamic previews during query preparation.

Data reflections feature acts as an intelligent caching layer, optimizing query performance and enabling low-latency dashboard refreshes for BI workloads.

The platform’s virtual datasets allow for complex query logic to be encapsulated and reused, supporting data-as-code principles such as Git-like version control and experimentation.


Cloud-native architecture offers elastic compute scaling and is available as a managed service on AWS and Azure, making it suitable for both on-premises and cloud deployments. It supports role-based access control and multitenancy, which is essential for enterprise environments with strong data governance requirements.

What do you dislike about the product?

The learning curve can be significant, especially when configuring advanced features like data reflections, multitenancy, and integrating with complex enterprise authentication systems.

While the UI is functional, some administrative and monitoring functions feel less intuitive compared to other modern analytics platforms.

I have also found that fine-grained access controls and tenant isolation require careful configuration to avoid inadvertent data exposure in multi-tenant scenarios.

What problems is the product solving and how is that benefiting you?

Dremio has eliminated the need for traditional ETL pipelines in my analytics workflows, allowing direct querying and data exploration across disparate sources without data movement.

This has resulted in faster dataset creation cycles and reduced bottlenecks between data engineering and analytics teams.

The platform’s autonomous performance optimization and use of data reflections have significantly improved query speeds, enabling real-time analytics and interactive BI dashboarding even on large, complex datasets.

By adopting Dremio, I achieved unified access to both structured and semi-structured data in a single platform, which streamlined data governance and cataloging.

The self-service model empowered business analysts to experiment and iterate on data products without constant engineering intervention, accelerating time-to-insight for AI and analytics projects.

The platform’s open, standards-based approach has also made it easier to integrate with existing tools and future-proof my data infrastructure against vendor lock-in concerns.


✅ My overall insight: Dremio has enabled a more agile, scalable, and cost-effective analytics environment, supporting both operational BI and advanced data science initiatives in a unified, governed, and performant manner.

What do you like best about the product?

I like the fact that you can query directly s3 and hdfs and it also support power bi as integration

What do you dislike about the product?

Its not etl friendly so I have to link it with apache ariflow

What problems is the product solving and how is that benefiting you?

The easy integration so i save time

What do you like best about the product?

its great experience using Dremio. I have used its sql query engine product. the implementation was very easy and good for freshers and non-tech people. it's not too expensive w.r.t to other platforms. I like the speed. it's quite fast. I like the customer support service.

What do you dislike about the product?

there is nothing which I dont like as I like it and its good to try on different platform for cloud and analytics work.

What problems is the product solving and how is that benefiting you?

I have used its sql query engine product. the implementation was very easy and good for freshers and non-tech people.
its very helpful for data analytics and visulizations.

What do you like best about the product?

It is super user friendly and helps to handle big ranges of data.

What do you dislike about the product?

Fairly speaking there is not a lot to say about that. Users can get what they expect from optimal data cloud.

What problems is the product solving and how is that benefiting you?

It helped a lot to me to combine different sources and process them together easily and faster.

What do you like best about the product?

The Reflections feature is awesome. It allows you to seamlessly accelerate queries by pre-aggregating query results at various aggregations that you can define over time, based on actual query usage. If you move away from Tableau, Dremio is how you can replace Tableau's Extract feature. Or, if you're using Superset, you can insert Dremio in between Superset and the data sources to auto-magically speed up slow queries and dashboards.

What do you dislike about the product?

Dremio OSS does not support encrypted ODBC or Flight connections. You need Enterprise for that.

What problems is the product solving and how is that benefiting you?

Speeding up slow Superset dashboards.