Dremio Pricing Overview

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Its just how easy it is to use. When we first onboarded, I was surprised at how fast we could connect to, like, multiple data sources. Didn't have a huge setup headache, which was awesome.The implementation wasn't that bad, especially comparing to some other BI tools we used. I mean, it wasn't 100% smooth, had a few little hiccups, but overall we got it running way easier than I expected.

It's got pretty rich feature set—the reflections and acceleration stuff is cool for performance, even if it feels a bit overwhelming at the start. Integrating it with our existing stuff, like our AWS S3 buckets and Snowflake, was pretty straightforward. No major drama there,Oh, and the SQL editor is way better than I thought it'd be..Overall, it just feels like a tool built for speed and flexibility. we use sometimes multiple times a day when I have to do ad-hoc analysis or explore big datasets Yeah, there's definitely a learning curve, no lie. But once you get past that, you realize how powerful it is. Review collected by and hosted on G2.com.

Their customer support is decent. Sometimes they take a bit to get back to you, but most of the time I've gotten a proper solution that actually fixes the problem. The performance is weird sometimes, like one day a query runs blazing fast, and then the next day the exact same query is just... slower. For no obvious reason, The UI also feels a little clunky at times, not gonna lie. Especially when you're trying to handle a really large dataset, it'll just freeze up for a second , laggy . Makes the whole experience feel less smooth than it should.And the documentation... yeah, it could definitely be better. A lot of times I've had to just google around on forums or actually reach out to support just to find some small configuration detail that should really be in the main docs. Wastes a bunch of time.

Also it's not exactly cheap. When you start to really scale it up, especially running on our own cloud infra, the bills start to add up. I feel like for smaller teams, the admin side of things can feel too complex for what you need. Just setting up user permissions and everything is a whole thing. Review collected by and hosted on G2.com.