Lakehouse platforms & table formats · Dremio Corporation

Dremio

SQL query and semantic layer engine for querying data lakes directly, built around Apache Iceberg and Apache Arrow.

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Dremio is a SQL lakehouse platform that lets analysts and BI tools query data sitting in cloud object storage, relational databases, and other sources directly, without first loading it into a warehouse. It is built on Apache Arrow for in-memory columnar processing and Apache Iceberg as its native table format, and adds a semantic layer of virtual datasets, reflections (materialized, auto-maintained accelerations), and governed spaces so teams can curate and reuse queries across the organization. Dremio is offered as Dremio Cloud, a fully managed service billed per Dremio Compute Unit (DCU), and as self-hosted Dremio Software for on-premises or private-cloud deployment. It competes with Starburst and Trino-based engines, and with warehouse vendors, for organizations wanting to query the lake instead of copying data into one.

At a glance

Vendor Dremio Corporation
Pricing model Usage-based
Free tier Yes
Deployment Cloud, Self-hosted
Open source No
Best for Teams wanting to run governed SQL analytics directly on lake data without a separate warehouse copy.

Pricing

Dremio Cloud is billed per Dremio Compute Unit (DCU) with a 30-day free-credit trial; Dremio Enterprise/Software pricing requires contacting sales.

Plan Price Notes
Dremio Cloud $0.20 per DCU Fully managed with automatic scaling and optimization; 30-day trial with $400 in credits
Dremio Enterprise Contact sales Self-hosted/private-cloud deployment

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • SQL query engine directly over data-lake and database sources
  • Native Apache Iceberg table format support
  • Apache Arrow-based in-memory columnar processing
  • Reflections: auto-maintained materializations for query acceleration
  • Semantic layer with virtual datasets and governed spaces
  • Data-as-code versioning via Nessie catalog integration
  • Cloud (managed) and self-hosted software deployment options

Integrations

Profile last reviewed September 21, 2026

Alternatives

Apache Iceberg Open-source table format that adds warehouse-style transactions, schema evolution, and time travel to data-lake files. Databricks Managed lakehouse platform, built by Apache Spark's creators, combining Spark-based compute with governance and ML tooling. Cloudera Data Platform Enterprise data platform unifying data engineering, warehousing, ML, and streaming across hybrid and multi-cloud environments.

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Terms to know

Data lakehouse A storage architecture that adds warehouse-style structure and transactions directly on top of low-cost data lake storage. Semantic layer A layer that defines business metrics and dimensions once, centrally, so every tool and report uses the same numbers. Self-service BI BI tooling that lets business users build their own reports and explore data without waiting on IT or analytics teams. Apache Iceberg An open table format adding ACID transactions, schema evolution, and time travel to files stored in a data lake. Query engine The software component that parses, plans, and executes queries against one or more data sources.

Related guides

How to choose a lakehouse platform Choosing a lakehouse means two decisions, not one — which open table format your data sits in, and which platform manages and queries it.