Sold by: DremioÂ
Vendor Insights
Dremio Cloud is the easy and open lakehouse platform.
Overview
Dremio Cloud is a fully-managed lakehouse platform. Data teams use Dremio to deliver self-service analytics, while enjoying the flexibility to use Dremio's lightning-fast SQL query service and any other processing engine on the same data.
Dremio Cloud enables analysts to explore and visualize data with sub-second query response times, and enables data engineers to ingest and transform data directly in the data lake with full support for DML operations. In addition, analysts can join data in the lake with data in external databases, so they don't have to move data into object storage to derive value from that data. Dremio's open lakehouse platform, based on community-driven standards like Apache Iceberg and Apache Arrow, enables organizations to use best-in-class processing engines and eliminates vendor lock-in.
With Dremio Cloud, organizations can focus on deriving value from data instead of database administration. As a fully-managed platform, Dremio Cloud eliminates the need to install, configure, and upgrade software, and manages the entire lifecycle of compute engines (including provisioning, scaling, pausing, and decommissioning). Dremio Cloud compute engines are deployed in your Amazon Virtual Private Cloud (VPC), so your data stays and is processed in your VPC.
To learn more about Dremio, visit https://www.dremio.com .
For custom pricing, EULA, or a private contract, please contact AWS-Marketplace@dremio.com for an AWS Private Offer.
Highlights
- SQL for Everyone: Deliver all the performance and functionality of a data warehouse directly on the data lake. Dremio's intuitive and self-service UI enables users to access more data and make better business decisions in a fraction of the time.
- Any Data: Enrich your analyses and blend lakehouse data that's not yet in the lake, with connectors to a variety of external databases. Create a single source of truth for your data that can be leveraged by all downstream users and apps.
- Fully-Managed: Focus on insights, not administration. Start in minutes with a lakehouse architecture, without worrying about software to install, configure, or upgrade. Scale automatically to meet the needs of your business.
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Dremio Consumption Units | 100 Cloud Platform Units to build, automate,& query lakehouse services | $39.00 |
Dimension | Cost/unit |
|---|---|
Overage consumption Units | $0.39 |
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Delivery details
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Support
Vendor support
Dremio Community Support: https://community.dremio.com/Â
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By Dremio
By Databricks, Inc.
By Cloudera
Top
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In Data Warehouses
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10
In Databases & Analytics Platforms, ML Solutions, Data Analytics
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In Data Analysis
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Data Lake Query Performance
Provides sub-second query response times using SQL query service on data lake platforms
Open Standards Support
Utilizes community-driven standards like Apache Iceberg and Apache Arrow for processing engines
Multi-Source Data Integration
Enables joining data from data lakes and external databases without data movement
Compute Engine Management
Automatically handles compute engine lifecycle including provisioning, scaling, pausing, and decommissioning
VPC-Based Data Processing
Deploys compute engines within customer's Amazon Virtual Private Cloud for secure data processing
Data Platform Architecture
Unified platform integrating data engineering, analytics, business intelligence, data science, and machine learning on a single architecture
Open Source Foundation
Built on open source data projects with support for open standards and data formats
Lakehouse Infrastructure
Provides a common data management approach using a lakehouse architecture running on Amazon S3
Data Intelligence Engine
Advanced engine capable of interpreting organizational data context and enabling broad data access across teams
Collaborative Workflow
Native collaboration capabilities enabling cross-functional data and AI workflow integration
Data Platform Architecture
Enterprise data platform supporting multi-cloud, hybrid cloud, and on-premises data management environments
Security and Governance Framework
Shared Data Experience (SDX) technology providing consistent security and governance policies across data workloads and infrastructures
Multi-Function Analytics
Integrated analytics platform supporting data ingestion, transformation, querying, optimization, and predictive modeling without requiring separate point products
Workload Optimization
Intelligent autoscaling capabilities for dynamically adjusting cloud infrastructure resources based on computational requirements
Data Lifecycle Management
Comprehensive platform supporting data processing across multiple services including Data Warehouse, Machine Learning, and custom analytics environments
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
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No security profile
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Standard contract
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Customer reviews
0 ratings
0 AWS reviews
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74 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Abhishek C.
Dremio make daily work easy, but needs little polish
Reviewed on Sep 10, 2025
Review provided by G2
What do you like best about the product?
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.
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.
What do you dislike about the product?
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.
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.
What problems is the product solving and how is that benefiting you?
So Dremio's basically solved our whole issue with data being scattered everywhere. Before this, we were always having to copy and move data into some central system just to be able to run a query on it. Super time-consuming .We can now just query right on top of where the data lives. Like, directly on S3, or Snowflake, even some of our old legacy databases. We don't need to build these massive ETL pipelines just for a simple question, which is a game changer.It's also helped a ton with speed. Those reflections they have? They make a huge difference on heavy queries. Our reporting team used to have to wait like, hours for their results to come back, and now it's way faster. Saves a ton of times for our day-to-day analysis and helps us make decisions way quicker.
Luca P.
Unified lakehouse platform for Analytics and Al
Reviewed on Jul 06, 2025
Review provided by G2
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.
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.
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.
âś… 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.
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.
âś… 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.
Information Technology and Services
Easy Direct Access
Reviewed on Jul 03, 2025
Review provided by G2
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
Aarti S.
Review for Dremio product
Reviewed on Jun 24, 2025
Review provided by G2
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.
its very helpful for data analytics and visulizations.
Sadi H.
Work
Reviewed on Jun 19, 2025
Review provided by G2
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.