The Agentic Lakehouse

Iceberg-Native Platform

Built on the open lakehouse standards Dremio co-created.

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Iceberg Made Easy

Autonomous optimization, no tuning.

No Lock-In

Open table format, not proprietary ones.

Interoperability

Read and write across any Iceberg REST engine.

20X faster than Snowflake on TPC-DS at 1TB

99 queries completed in 22 seconds on an 8-node m7gd.4xlarge cluster
with zero tuning.

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CAPABILITIES

Iceberg Capabilities

Each component was designed for Iceberg from the start. That architectural decision shows up in capabilities no other platform can replicate.

Why Teams Choose Us

Arrow-based SQL Engine for Iceberg

  • Built on Apache Arrow (columnar in-memory format) with LLVM code generation (Gandiva) and C3 columnar cloud cache on NVMe SSDs
  • Processes Iceberg/Parquet data in vectorized batches without converting to a proprietary internal format.
  • Arrow Flight for high throughput Iceberg data transfer
  • Elastic scale for concurrency and optimized price-performance
Why Dremio is the Best SQL Engine for Apache Iceberg →

Autonomous Reflections

  • Observes query patterns to automatically create materializations for query acceleration
  • Optimizer rewrites queries transparently, no code or query changes needed
  • Automatically refreshes, and retires materializations
    to optimize performance and cost
  • Incremental refresh, ensuring fresh data at low resource costs
Learn More about Autonomous Reflections →

Native Iceberg Clustering

  • Z-order clustering co-locates data across multiple columns simultaneously. No partition explosion, no small file sprawl
  • Two-level pruning skips files at the Iceberg manifest level and row groups via Parquet column stats, minimizing I/O on every query
  • Clustering Depth tracking rewrites only degraded file regions, never the full table
  • Parquet row group statistics skip irrelevant rows within each file
  • Incremental, batched execution makes clustering safe to run continuously on petabyte-scale tables
Dive Deeper into Iceberg Clustering →

Open Catalog (Powered by Polaris)

  • Read and write with any REST-compatible engine: Dremio, Spark, Flink, Trino, DuckDB, all sharing the same Iceberg tables
  • RBAC with row-level filters and column masking enforced at the catalog, consistently across every engine
  • Centralized metadata management for Iceberg lakehouse environments
  • Just-in-time credential vending issues temporary, scoped storage credentials per query, keeping keys out of engines
  • A single catalog can span multiple storage buckets and locations across clouds.
Learn More About Dremio’s Open Catalog →

Support for Iceberg v3

  • Read / Write V3 Tables: Latest Iceberg spec read and write
  • Deletion Vectors: Faster row deletes, and accelerated reads
  • VARIANT Support: JSON and semi-structured data analysis
  • Row-Level Lineage: Row-level creation and update tracking
Explore More around Dremio and Iceberg V3 →

Automatic Table Maintenance

  • Compaction, snapshot expiry, and orphan file cleanup run on a schedule
  • VACUUM automatically removes expired snapshots and orphan files
  • Policy-based rules govern file size targets and snapshot retention per table, with no manual intervention required
Explore Dremio’s Auto Table Maintenance Capabilities →

COMPARE

How Dremio Stacks Up

Dremio Snowflake Databricks
SQL Engine for Iceberg
Arrow-native. No format conversion.
Proprietary engine. Converts Iceberg to internal format. Delta-optimized. Iceberg via compatibility layer.
Autonomous Query Acceleration
Autonomous Reflections
Proprietary only, not for Iceberg Proprietary only, not for Iceberg
Native Iceberg Clustering
Automatic Z-order. Petabyte-scale safe.
Proprietary format, separately metered Iceberg in Preview only
Open Catalog
Apache Polaris. Multi-Engine Iceberg REST R/W.
Managed Polaris sidecar. Cannot write to own tables. Unity Catalog. Proprietary + OSS variant. Not Iceberg-native.
Iceberg V3
GA. Deletion Vectors, VARIANT, Row-Level Lineage.
Preview Preview
Auto Table Maintenance
Policy-based. No manual intervention.
Managed tables only Unity Catalog required
Dremio Cloud
SQL Engine for Iceberg Arrow-native. No format conversion.
Autonomous Query Acceleration Autonomous Reflections
Native Iceberg Clustering Automatic Z-order. Petabyte-scale safe.
Open Catalog Apache Polaris. Multi-Engine Iceberg REST R/W.
Iceberg V3 GA. Deletion Vectors, VARIANT, Row-Level Lineage.
Auto Table Maintenance Policy-based. No manual intervention.

LEADERS IN OPEN SOURCE

The Lakehouse OSS Standards

Driving innovation in the open-source community with contributions to Arrow, Iceberg, and Polaris.

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Co-created by Dremio, Apache Arrow is the in-memory and transport format that powers high-performance lakehouse analytics.

As a key contributor, Dremio helps drive Apache Iceberg, the open table format for reliable and scalable lakehouse data.

Apache Polaris, co-created by Dremio, is an open metadata catalog designed for modern lakehouse architectures.

FAQs

Apache Iceberg FAQ

Get common questions answered about Apache Iceberg.

Apache Iceberg is an open standard table format that enables ACID-compliant transactions, time travel, partition pruning, and schema evolution for reliable, high-performance analytics at petabyte scale.

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Apache Iceberg: The Definitive Guide

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The Iceberg-Native Advantage

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Why Apache Iceberg Is the Future of Data Lakes

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