--- title: Dremio Reviews meta_title: 'Dremio Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 71 reviews by the users' company size, role or industry to find out how Dremio works for a business like yours. aggregate_rating: rating_value: 4.6 review_count: 71 scale: '5' date_modified: '2026-08-09' parent_category: name: Big Data url: https://www.g2.com/categories/big-data --- # Dremio Reviews **Vendor:** Dremio **Category:** [Big Data Processing And Distribution Systems](https://www.g2.com/categories/big-data-processing-and-distribution) **Average Rating:** 4.6/5.0 **Total Reviews:** 71 ## About Dremio Dremio is the pioneer of The Agentic Lakehouse—the only data platform built for agents, managed by agents. Organizations need to transform ideas into actions at unprecedented speed—Dremio delivers this agility by equipping AI agents with federated data access, unstructured data processing, and rich business context through its AI Semantic Layer. In the agentic-era, data engineering teams can’t manually tune performance for thousands of users and agents asking unpredictable questions every second. Dremio’s Agentic Lakehouse autonomously manages itself, removing undifferentiated management tasks, allowing engineers to focus on initiatives that drive business results. Dremio’s agentic lakehouse automatically optimizes queries, reorganizes data, and maintains performance at any scale. Dremio is trusted by thousands of global enterprises including Shell, TD Bank, and Michelin, and built on open standards. Dremio co-created Apache Polaris and Apache Arrow, and it's the only lakehouse built natively on Apache Iceberg, Polaris, and Arrow. ## Dremio Pros & Cons **What users like:** - Users find Dremio's **ease of use** exceptional, enabling quick data sharing and seamless integration with multiple tools. (13 reviews) - Users appreciate the **seamless integrations** of Dremio with tools like Power BI and Tableau for efficient data management. (10 reviews) - Users value the **exceptional performance** of Dremio for accelerating query speed and facilitating efficient data workflows. (7 reviews) - Users value the **SQL support** in Dremio, enhancing data connectivity and integration with various analytics platforms. (7 reviews) - Users appreciate the **advanced data management capabilities** of Dremio, enhancing data collection and analysis across various platforms. (6 reviews) - Users commend Dremio for its **excellent handling of large datasets** , enabling fast and scalable data management efficiently. (6 reviews) - Setup Ease (6 reviews) - Speed (6 reviews) - Users appreciate the **ease of use** of Dremio, enabling quick connections to multiple data sources without hassles. (5 reviews) - Features (5 reviews) **What users dislike:** - Users find the **initial setup complicated** and experience a steep learning curve that hampers their productivity. (5 reviews) - Users report that **customer support can be slow** , leading to delays in resolving issues and frustration. (5 reviews) - Users note a **steep learning curve** with Dremio, making setup and feature understanding challenging for beginners. (4 reviews) - Users find the **difficult setup** of Dremio challenging and time-consuming, often requiring external resources for assistance. (3 reviews) - Users feel that the **documentation is poor** , often forcing them to seek help outside the provided resources. (3 reviews) - Users report **connectivity issues** in Dremio, particularly with missing features and limited support for connections. (2 reviews) - Debugging Issues (2 reviews) - Error Handling (2 reviews) - Expensive (2 reviews) - Increased Costs (2 reviews) ## Dremio Reviews ### 1. Dremio make daily work easy, but needs little polish **Rating:** 4.0/5.0 stars **Reviewed by:** Abhishek C. | Associate Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** September 09, 2025 **What do you like best about Dremio?** 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. **What do you dislike about Dremio?** 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. **What problems is Dremio 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. ### 2. Dremio is an excellent semantic layer and caching/acceleration/extract layer **Rating:** 4.0/5.0 stars **Reviewed by:** Josh C. | Online and Platform Services Director, Mid-Market (51-1000 emp.) **Reviewed Date:** October 22, 2024 **What do you like best about Dremio?** 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 Dremio?** Dremio OSS does not support encrypted ODBC or Flight connections. You need Enterprise for that. **What problems is Dremio solving and how is that benefiting you?** Speeding up slow Superset dashboards. ### 3. Data Engineer with 2 years experiences with Dremio **Rating:** 4.0/5.0 stars **Reviewed by:** NGUYEN C. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** October 17, 2024 **What do you like best about Dremio?** Virtualization data , also the open sources like Arrow, Iceberg. **What do you dislike about Dremio?** sometimes I had the OOM error and dont' know exactly why **What problems is Dremio solving and how is that benefiting you?** Data virtualization. that helps us a lot because at RTE, we have many different databases ### 4. quick queries with a few issues. **Rating:** 4.0/5.0 stars **Reviewed by:** rene d. | Senior Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** October 10, 2024 **What do you like best about Dremio?** with reflections, queries execute quickly. functions with a wide variety of data formats. appearance is good. personalisation is a plus for me. **What do you dislike about Dremio?** Sometimes software makes mistakes. Customer assistance is slow. **What problems is Dremio solving and how is that benefiting you?** our data analysis duties are completed more quickly. now, we can provide clients with insights more quickly. ### 5. Good enterprise version bad open source **Rating:** 4.0/5.0 stars **Reviewed by:** Nelson N. | Analista de dados, Mid-Market (51-1000 emp.) **Reviewed Date:** October 18, 2024 **What do you like best about Dremio?** Easily centralizing data, with many sources and resources **What do you dislike about Dremio?** High difficult to mantain the environment, high resources demands **What problems is Dremio solving and how is that benefiting you?** Centralizing data ### 6. Dremio Adoption experience **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Consumer Services | Enterprise (> 1000 emp.) **Reviewed Date:** May 10, 2024 **What do you like best about Dremio?** The product concept is straightforward and easy to explain. Deploying/upgrading is simple especially with K8 deployments. Open tech stack with Iceberg and Arrow is a big advantage **What do you dislike about Dremio?** Learning curve is high. Teams need services help to succesfully deploy. More debug and self management will help in adopting and maintaining. This is critical for middleware technologies Ease of integration has been a challenge expecially with the choice of BI Platform **What problems is Dremio solving and how is that benefiting you?** Abstraction to facilitate single source of truth. Ability to control and manage queries at scale is beneficial. ### 7. Evaluating platform for data management and delivery **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Financial Services | Enterprise (> 1000 emp.) **Reviewed Date:** May 02, 2024 **What do you like best about Dremio?** Apache Iceberg and Apache Arrow interoperability **What do you dislike about Dremio?** On-Premise Deployment and stability issues **What problems is Dremio solving and how is that benefiting you?** Delivering content and query capability to clients ### 8. Great Tool to bring many data sources of Big Data together with good performance **Rating:** 3.5/5.0 stars **Reviewed by:** manish J. | Mid-Market (51-1000 emp.) **Reviewed Date:** February 16, 2023 **What do you like best about Dremio?** Its easy to configuring many different sources and create virtual data set that do unions across them. I am really happy about performance for data-retrieval **What do you dislike about Dremio?** There are so many bugs in each versions , So that we have to keep them updated with new release **What problems is Dremio solving and how is that benefiting you?** Dremio has a feature to make data accessible and usable by a much larger number of users . And reflections feature to make it so easy ### 9. Revolutionary technology with a natural user interface **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Oil & Energy | Mid-Market (51-1000 emp.) **Reviewed Date:** October 25, 2021 **What do you like best about Dremio?** Dremio initially caught my eye because the company grew out of the open-source arrow project, which was already a fantastic project and critical to big data platforms. Dremio does one thing really well and a couple of other things pretty well: - To start with, with regards to scalable data access, whether you're accessing terabytes of parquet/files or megabytes of database information, Dremio _just works_. There are very few other solutions that 1) allow you to join different data sources on-demand, 2) do _not_ run 24/7 but spin up clusters when you need them and 3) have a reasonably user-friendly interface. The combination has made Dremio crucial to increasing productivity at my company. However, Dremio offers even more than the killer feature of easy data access described above: - Good mechanisms for data governance, including internal lineage graphs between datasets - Ways to structure computing resources with regards to finetuning query performance -- if you need dashboard datasets to perform more quickly than UI datasets, it's almost a point-and-click operation - You can expose internal statistics on usage and performance for all queries - Better and better granularity with regards to managing users - Most tools only allow users to download a max of 1-10k rows of data. Dremio easily allows 1 million rows and performs on this as well Dremio has really thought about how companies should manage and expose data and has made sure to provide a design and the technology to make data access, democritization and governance easier. **What do you dislike about Dremio?** Dremio is still a young company and while the product works well, they're still working very hard at improving it. We have not yet run into a single bug on production, but it was initially noticeable that it's a young product (start 2021). Fortunately, they are rapidly making new releases and fixing a lot of the little issues so that the product has a good, professional level of quality. **Recommendations to others considering Dremio:** Dremio is more expensive for smaller organizations -- even though we are smaller and it is thus more expensive for us, it's been able to solve problems that cheaper solutions were not capable of, in particular easy, scalable, manageable performant data access. **What problems is Dremio solving and how is that benefiting you?** As I mentioned above, Dremio solves data access in a performant, easy way -- and much easier, faster and in a smarter way than any other tool that I've yet to come across in 2021. ### 10. Handy engine to bring many sources of Big Data together with good performance **Rating:** 4.0/5.0 stars **Reviewed by:** Julien L. | Data Services Lead, Mid-Market (51-1000 emp.) **Reviewed Date:** July 21, 2021 **What do you like best about Dremio?** I really like the ease of configuring many different sources and create views that do unions across them. I'm also a big fan of Flight's performance for data-retrieval! **What do you dislike about Dremio?** Dremio isn't an industry standard (yet), so help on the official forums or rest of the internet can be quite limited. **What problems is Dremio solving and how is that benefiting you?** We're aiming to offer a single view, that exposes near-live intraday data (in low-latency storage solutions) as well as far-back history (in high-bandwidth Big Data stores). We try to make it as easy, transparent and performant as possible for users to access any data we store internally. ### 11. Dremio is really cool! **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Entertainment | Mid-Market (51-1000 emp.) **Reviewed Date:** May 28, 2021 **What do you like best about Dremio?** With a tiny engineering team (1) we were able to get Dremio up and running in AWS for our org to start using. It is extremely easy to bring silos of data from all over the organization held in various formats and make them available in our platform. Once in the platform, it provides a non-threatening interface to allow both analysts and non-analysts the ability to search, find and query the data for their use cases. Dremio has done a wonderful job! **What do you dislike about Dremio?** Dremio definitely puts the "democracy" in "data democratization", but I wish there were more tools to allow a little more control of what data sources are made public on the platform. An organization wouldn't want to be too strict over who can do things in this powerful platform, but being too open could result in data confusion. Data governance tools to help make sure appropriate documentation or tagging are provided or possibily a request/approval workflow before something is made public to everyone would be really nice. **Recommendations to others considering Dremio:** If you are looking for a centralized data platform for your org, you should include Dremio in your evaluations. Definitely worth your time learning more about. **What problems is Dremio solving and how is that benefiting you?** The biggest problem we are solving is around the data silos in our organization. Dremio allows us to make data accessible and usable by a much larger population. ### 12. Had a great experience building our Data Virtualisation layer with Dremio on top of our Data Lake. **Rating:** 4.0/5.0 stars **Reviewed by:** Shayen Y. | Senior Data Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** June 10, 2021 **What do you like best about Dremio?** Lightning-fast query speeds, ability to easily work with data lakes **What do you dislike about Dremio?** Intermittent issues, needs to be tested on a wider range of datasets **Recommendations to others considering Dremio:** Dremio is most suitable for organizations with huge volumes of data (in 100s of GBs). That is also when you will be able to see the value of Dremio vs a traditional Data Warehouse **What problems is Dremio solving and how is that benefiting you?** Moving from Data Warehouse to Lakehoue ### 13. My Dremio experience as enterprise-wide data platform by big German client **Rating:** 4.0/5.0 stars **Reviewed by:** Andrej S. | Managing Delivery Architect, Insights&Data, Enterprise (> 1000 emp.) **Reviewed Date:** November 20, 2020 **What do you like best about Dremio?** Dremio helps us a lot to manage a high workloads from our reportnig systems and achieve a fast response time for more then 500 management dashboards. Many of our end-users like work with Dremio to avoid additional Data Engineering skills in team. For some of them it was surprisely fast after changing the Reporting from "Import" to "live" connection to move data processing directly to Dremio. But the most demanded feature was Reflections which gave sometimes lightning-fast (less then 1 second) response time without any re-engineering of business logic or reducing the data volumes. In case of any issues and challenges Dremio was very cooperative on Germany and global level to solve it. **What do you dislike about Dremio?** As Dremio do not implemented Elastic Engine on Azure we need to maintain Kubernetes cluster to reach out needed ad-hoc scale-out requirements. **Recommendations to others considering Dremio:** Based on my exprerience Dremio fits for usecases when you: ..have Multi-Cloud stategy and want to avoid "lock-in" effect into one of cloud-vendor solution ..have onPremise Hadoop cluster or ODS store which performance is not enough ..have end users which wants to work directly with data, but have only SQL knowlegde ..want to offload data processing to Dremio from you BI-tools like Tableau or Power BI ..have usecases where time-to-market has a huge value (like a ad-hoc data exploration in Data Science) **What problems is Dremio solving and how is that benefiting you?** We have a different use cases on the same shared Dremio instance - "classical" Management Reporting, Self Service BI, Data exploration, AI Use Cases and Business Process Automation. So our worloads ware not equal in time and not always predictable from "big-bang" requests and high-volume scans. But Dremio managed it in smooth way. ### 14. A new way for simplification **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Chemicals | Enterprise (> 1000 emp.) **Reviewed Date:** November 25, 2020 **What do you like best about Dremio?** Simplification – Single point of data access. Data Blending – Merge diverse data pools easily Protection – Enable security and authorization. Acceleration – Performant reporting and analysis **What do you dislike about Dremio?** Different roadmap AWS and Azure and not all capabilities you have in AWS are in Azure **What problems is Dremio solving and how is that benefiting you?** We organized the Lake like a virtual LAB or APP. In a APP we provide for all our user the correct folder structure and all the resources they need to analyze data. Dremio use the Data lake as a data source . From outside, Dremio looks and behaves like a relational Database ### 15. Data Lake Adoption **Rating:** 4.0/5.0 stars **Reviewed by:** Gurdeep S. | Mid-Market (51-1000 emp.) **Reviewed Date:** December 04, 2020 **What do you like best about Dremio?** Enabling interactive speed queries on Hadoop **What do you dislike about Dremio?** Can be misused as a mainstream ELT tool. **What problems is Dremio solving and how is that benefiting you?** Making Hadoop as the mainstream data platform for all consumers. This tool has really flattened the Change management curve for the BI community in adopting the Data Lake on Hadoop ### 16. A virtual integration environment to allow data analyzing on a higher and faster level **Rating:** 4.0/5.0 stars **Reviewed by:** Bert K. | Mid-Market (51-1000 emp.) **Reviewed Date:** November 30, 2020 **What do you like best about Dremio?** Easy to use, SQL based, No data movement, optimizing and integrate queries and/or the use of reflections for a high analyzing performance **What do you dislike about Dremio?** At this moment no actual issues, maybe a missing data dictionary **What problems is Dremio solving and how is that benefiting you?** No data movement, self service analytics ## Dremio Discussions - [What is a Dremio reflection?](https://www.g2.com/discussions/what-is-a-dremio-reflection) - 1 comment - [View Dremio pricing details and edition comparison](https://www.g2.com/products/dremio/reviews?filters%5Bnps_score%5D%5B%5D=4§ion=pricing&secure%5Bexpires_at%5D=2026-08-13+14%3A17%3A01+-0500&secure%5Bsession_id%5D=45a7f7dd-1ad1-45b5-b819-c6bd55e50c87&secure%5Btoken%5D=ba74cf91a8cd4a848e256c93679decfc094988a6f9fc1768945c20bac622e67e&format=llm_user) ## Dremio Integrations - [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) - [Microsoft SharePoint](https://www.g2.com/products/microsoft-sharepoint/reviews) ## Dremio Features **Reports** - Reports Interface - Steps to Answer - Graphs and Charts - Score Cards - Dashboards - Customizable Reports - Marketing Reports - Sales Reports - Activity Dashboard - Interactive Reports - Customizable Reports - Customizable Reports - Activity Dashboard - Customizable Dashboard **Data Management** - Data Integration - Data Compression - Data Quality - Built-In Data Analytics - Data Lake Analytics - ETL - Extract Transfer Load - Data Capture and Transfer - Real-Time Analytics - Reporting/Analytics **Data Management** - Data Migration - Managing Data **Deployment & Integration - Semantic Layer Tools** - Multi-Environment & Multi-Cloud Support - Open API & SDK Integration **Data Transformation** - Data Querying - Reporting/Analytics - Predictive Analytics - Visual Analytics **Integration** - BI Tool Integration - Data lake Integration **Data as a Service** - Self-Service Isights - DaaS Quality **Data Connectivity & Federation - Semantic Layer Tools** - Cross-Source Query Federation - Dynamic Schema & Metadata Adaptation **Integrations** - Hadoop Integration - Spark Integration **Deployment** - On-Premise - Cloud **Architecture** - Data Fabric Creation - DaaS Architecture **Data Modeling & Metrics - Semantic Layer Tools** - Derived & Calculated Metrics - Time Intelligence Functions **Platform** - Machine Scaling - Data Preparation - Spark Integration **Connectivity** - Hadoop Integration - Multi-Source Analysis - Data Lake - Real-Time Data - Data Capture and Transfer - Trend Analysis - What-if Analysis - Statistical Analysis - Data Blending - Ad hoc Analysis - Third-Party Integrations **Performance ** - Scalability **Performance Optimization - Semantic Layer Tools** - Query Caching & Acceleration - Adaptive Query Optimization **Self Service ** - Calculated Fields - Data Column Filtering - Data Discovery - Search - Collaboration / Workflow - Automodeling - Natural Language Search - Visual Discovery - Data Blending - Data Blending **Processing** - Cloud Processing - Workload Processing **Operations** - Data Visualization - Data Workflow - Governed Discovery - Embedded Analytics - Notebooks - Data Discovery **Security** - Data Governance **Governance - Semantic Layer Tools** - AI Governance & Observability - Metric Lineage for AI Training Data - Version Control & Change Impact Analysis **Additional Functionality** - Data Warehousing - Drag & Drop - Activity Dashboard - Data Connectors - Ad hoc Reporting - Customizable Reports - Alerts/Escalation - Templates - Forecasting - Data Migration - Data Transformation - Access Controls/Permissions - API - Data Cleansing - Data Synchronization - AI Copilot - Dashboard Creation - Data Extraction - Data Security - SSL Security - Collaboration Tools - No-Code - High Volume Processing - Database Support - Search/Filter - Generative AI **Advanced Analytics** - Predictive Analytics - Data Visualization - Big Data Services - Real-Time Analytics - Reporting/Analytics - Real-Time Analytics - Reporting/Analytics - Visual Analytics **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **Advanced Intelligence - Semantic Layer Tools** - Natural Language Query Interface - Semantic Layer for AI/ML Models - Recommendation Engine **Additional Functionality** - Parallel Processing - Ad hoc Analysis - Multiple Data Sources - API - In-Database Processing - Monitoring - Real-Time Reporting - Data Synchronization - Real-Time Monitoring - Data Connectors - Performance Metrics - Ad hoc Reporting - Alerts/Notifications - Access Controls/Permissions - Drag & Drop - Data Visualization - Data Import/Export - Match & Merge - Data Transformation - Secure Data Storage - Data Extraction - AI Copilot - Customizable Reports - Activity Dashboard - Data Migration - In-Memory Processing - Data Mapping **Agentic AI Enablement - Semantic Layer Tools** - Agentic Query Orchestration - Contextual Reasoning Layer - Workflow Automation via Semantic Agents **Building Reports** - Data Transformation - Data Modeling - Integration APIs - Real-Time Data - Real-Time Data - Third-Party Integrations - Third-Party Integrations **Platform** - User, Role, and Access Management - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications - Mobile Access - Metadata Management **Additional Functionality** - Customizable Branding - Natural Language Processing - Data Extraction - AI Copilot - Ad hoc Reporting - Real-Time Reporting - Publishing/Sharing - Collaboration Tools - Strategic Planning - Self Service Data Preparation - Trend Analysis - Text Analysis - Real-Time Monitoring - Data Synchronization - Widgets - Benchmarking - Performance Metrics - Data Mapping - Generative AI - Trend/Problem Indicators - Customizable Templates - Access Controls/Permissions - Data Import/Export - Profitability Analysis - OLAP - Alerts/Notifications - Search/Filter - Drag & Drop - Data Connectors - Multiple Data Sources - Key Performance Indicators - Dashboard Creation - Role-Based Permissions - Data Mining - Forecasting - Ad hoc Query ## Top Dremio Alternatives - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (1,337 reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - 4.6/5.0 (714 reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,145 reviews)