2,000 +
Companies
Lowest Cost & Fastest Performance
Dremio Pricing
Fastest queries. Lowest cost. Highest productivity.
Fully managed agentic lakehouse on AWS (Azure coming soon). Zero infrastructure, automatic updates.
$0.20
per DCU (Dremio Compute Unit)
- Fully managed with automatic scaling and optimization
- Query your data in minutes, no manual configuration required
- Automatic feature releases, no upgrades or downtime
Complete control and customization, deploy anywhere with full flexibility over infrastructure, security, and compliance.
Contact Sales
Contact our sales team for pricing information.
- Self-manage security, compliance, and data policies
- Flexible deployment on cloud, Kubernetes, on-prem or Dremio-as-a-Service (DaaS)
- Integrates with your existing infrastructure and tools
150,000 +
Users
10 x
Productivity
99.99 %
Uptime
TRUSTED BY:
COMPARISON
Full feature comparison
Everything you need to know about what's included in each plan.
Criteria
Dremio Cloud
Fully managed
Dremio Enterprise
Self-hosted
AI Agent
AI Semantic Layer
Intelligent Query Engine
Open Catalog
Infrastructure Management
Dremio-managed
Self-managed
Supported Infrastructure
AWS (Azure Coming Soon)
K8S (On prem) or Cloud (AWS, Azure, GCP)
Upgrades
Automatic
Manual
Scalability
Automatic
Manual
Pricing Model
Consumption based
Consumption based
Free Trial
$400 credit for 30 days
Talk to Sales
Security
Enterprise Ready
Enterprise Ready
Best For
Teams wanting a zero-maintenance, cloud-native experience and fast time to value.
Organizations needing full control, on-prem requirements, or strict compliance constraints.
Dremio Cloud
Fully managed
Dremio Enterprise
Self-hosted
Learn more about feature comparison and details on Dremio’s products.
GET STARTED
Take the next step with Dremio
See Dremio in Action
Explore this interactive demo and see how Dremio’s Agentic Lakehouse powers AI and BI workloads.
GET STARTED
Take the next step with Dremio
See Dremio in Action
Explore this interactive demo and see how Dremio’s Agentic Lakehouse powers AI and BI workloads.
RESOURCES
Running Snowflake, Redshift, or Databricks?
How Dremio works alongside the warehouse you already run to slash compute and query costs.
Shift Dashboards off Redshift and Cut Costs 40-60%
Dremio provides an alternative: keep Redshift for the workloads that need it, but offload the repetitive, expensive dashboard and reporting queries to Dremio's engine. Dremio's Autonomous Reflections serve those queries from Apache Iceberg tables on your own S3 storage, bypassing Redshift compute entirely. The result is a 40-60% reduction in Redshift compute costs in the first month, without migrating a single table.
Offload Snowflake Dashboards. Lower Spend Fast
Dremio provides a different approach. Instead of replacing Snowflake entirely, you can layer Dremio on top of it, offloading the expensive, repetitive queries to Dremio's engine while keeping Snowflake for the workloads it handles best. Dremio's Autonomous Reflections, AI-powered analytics, and federated query engine reduce the compute Snowflake needs to process, often cutting the bill by 40-60% in the first month.
Keep Databricks for ETL. Cut Analytics Costs.
Dremio's Agentic Lakehouse provides an alternative for the workloads that drive the highest Databricks spend: interactive analytics, BI dashboards, and ad-hoc queries. By offloading these queries to Dremio's engine with Autonomous Reflections, you eliminate the DBU consumption and the underlying cloud compute for 60-80% of your analytical workload. Meanwhile, Databricks stays in place for the heavy processing it does well: ETL pipelines, ML training, and Spark-based transformations.
Dremio is built for efficiency at every layer. As a data lakehouse, it runs queries directly on open formats in your object storage, eliminating the data copies, proprietary storage fees, and constant ingest pipelines that drive up costs elsewhere. That lean approach to data management, paired with automatic query acceleration, is what makes Dremio one of the most cost-effective data lakehouse solutions available today.
A Dremio Compute Unit (DCU) measures engine runtime, including query execution, Reflections, background processing, and platform overhead. DCU pricing is time-based, not per query, calculated as engine size × minutes running (e.g., a 20-DCU engine running for 10 hours consumes 200 DCUs). Infrastructure costs are fully included in DCU pricing.
Yes. Dremio Cloud includes a 30-day free trial with $400 in credits, no credit card required. It’s enough to connect your data, run real queries, and evaluate Dremio for your team.
For Dremio Enterprise, Contact Sales.
Your costs depend on query volume, concurrency, and the size of your data. Dremio’s consumption-based model means you only pay for what you use.
Dremio Cloud is the fastest way to get started. It’s fully managed on AWS with zero infrastructure overhead. Dremio Enterprise is built for organizations that need full control over deployment, security, and compliance, whether on-premises, Kubernetes, or their own cloud environment.
Yes. Dremio Cloud is available pay-as-you-go at $0.20 per DCU, so you only pay for what you use. For teams with predictable workloads or higher volume, annual contracts are available with committed pricing.
Dremio uses a simple, consumption-based model priced in Dremio Compute Units (DCUs), so costs scale directly with the work you run. Unlike Snowflake and Databricks, Dremio doesn’t mark up storage. Your data stays in your own lakes and data warehouses, under your control.
That separation keeps data analytics budgets predictable, because compute and storage charges never get bundled into a single, opaque invoice.
Cost changes in Dremio are driven almost entirely by compute usage. As workloads expand through feature scaling (larger datasets, more users, heavier queries), DCU consumption rises in step. Machine learning workloads and heavy ad-hoc exploration are typically the biggest sources of spend growth. Frequent data pipelines and reflection refreshes also add incremental cost, though far less than you’d see in a traditional warehouse. Finally, querying large volumes of raw data without acceleration will consume more DCUs. This is where Dremio’s reflections dramatically cut spend.
Dremio’s consumption-based model is designed for platform scalability. Whether you’re connecting new data sources, adding users, or expanding your storage solution, you only pay for the compute you actually use, measured in DCUs. Clusters auto-scale up during peak demand and spin down when idle, so your bill grows with real value delivered, not seat counts or over-provisioned capacity.
Want to see what makes Dremio the best data lakehouse for cost efficiency? Book a demo today.
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Enterprise-grade support to keep your platform running smoothly.
