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Dremio

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69 reviews
  • 1 profiles
  • 5 categories
Average star rating
4.6
Serving customers since
2015
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Dremio Reviews

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Abhishek C.
AC
Abhishek C.
Java SpringBoot Backend Developer | ReactJS
10/06/2025
Validated Reviewer
Review source: Organic

Dremio make daily work easy, but needs little polish

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.
Luca P.
LP
Luca P.
CTO - Growth Marketer full stack #MarTech | ⚡️ SaaS Advisor
07/06/2025
Validated Reviewer
Review source: Seller invite
Incentivized Review

Unified lakehouse platform for Analytics and Al

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.
Verified User in Information Technology and Services
CI
Verified User in Information Technology and Services
07/03/2025
Validated Reviewer
Review source: G2 invite

Easy Direct Access

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

About

Contact

HQ Location:
Santa Clara, California

Social

@dremio

What is Dremio?

Dremio is the unified lakehouse platform for self-service analytics and AI, serving hundreds of global enterprises, including Maersk, Amazon, Regeneron, NetApp, and S&P Global. Customers rely on Dremio for cloud, hybrid, and on-prem lakehouses to power their data mesh, data warehouse migration, data virtualization, and unified data access use cases. Based on open source technologies, including Apache Iceberg and Apache Arrow, Dremio provides an open lakehouse architecture enabling the fastest time to insight and platform flexibility at a fraction of the cost.Dremio was founded in 015 and is headquartered in Santa Clara, CA. Investors include Lightspeed Venture Partners, Redpoint, Norwest Venture Partners, Insight Partners and Sapphire Ventures. Connect with Dremio on GitHub, LinkedIn, Twitter, and Facebook.

Details

Year Founded
2015