3 Reasons Why Dremio Is the Best SQL Query Engine for Apache Iceberg

Dremio is a cutting-edge Lakehouse Platform designed to make data more accessible and actionable. With Apache Iceberg tables as first-class citizen, Dremio offers a powerful combination of data virtualization and unification capabilities. This means you can seamlessly combine data from databases, data warehouses, data lakes, and lakehouses into a single, governed platform. Dremio’s built-in semantic layer further ensures consistency, governance, documentation, and acceleration across your data ecosystem, enabling a wide range of use cases, from AI and BI to developing advanced data applications.

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A unique advantage of Dremio is its special relationship with Apache Iceberg, a powerful table format designed for modern data lakehouses. Whether managing structured or semi-structured data, Dremio enhances your ability to work with Iceberg tables efficiently and effectively. Here, we’ll explore three compelling reasons why Dremio is the best SQL query engine for Apache Iceberg tables.

Reason #1 - Performace

Dremio stands out as an industry leader in price-to-performance efficiency due to its deep integration with Apache Arrow. Developed initially in part as Dremio’s in-memory data format, Apache Arrow supercharges the platform’s ability to load and process data from the Parquet files that form the backbone of your Apache Iceberg tables. This architecture ensures speedy and efficient data processing, making Dremio an unparalleled choice for Iceberg workloads.

Dremio’s raw performance isn’t just about speed—it’s about optimizing every stage of the query lifecycle. Its columnar cloud cache (C3) ensures that regularly accessed data is cached for faster retrieval. The results cache accelerates repeated queries, and using Apache Calcite Dremio delivers advanced SQL query optimization. Combined, these features feed into a massively parallel processing engine, enabling swift execution of complex queries.

Moreover, Dremio’s capabilities extend beyond Iceberg tables. Its query engine can federate data across multiple sources—databases, data warehouses, and data lakes—at scale. This means you can execute queries that join and analyze disparate datasets as if they were a single, unified source, all with the performance and reliability you expect from a modern data lakehouse platform.

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Reason #2 - Acceleration

Dremio doesn’t just rely on its raw performance to deliver fast query results—it redefines query acceleration with its Reflections feature. Reflections eliminate the need for traditional approaches like materialized views and BI cubes, which are often cumbersome and expensive to maintain. Instead, Reflections allow you to precompute optimized representations of your data, significantly speeding up queries on large datasets.

What makes Reflections even more powerful is Dremio’s support for incremental and live refreshes. When your underlying Iceberg tables are updated, Dremio can incrementally update the corresponding Reflections, ensuring that the acceleration layer remains fresh and accurate with minimal computational overhead. This approach balances speed and cost-efficiency, enabling your organization to perform consistently for real-time analytics and BI use cases.

With Reflections, you can confidently scale analytics on massive datasets, knowing that query acceleration is automatically handled without requiring complex configurations or expensive infrastructure investments. This ensures faster results and a seamless experience for end-users across AI, BI, and other data-driven applications.

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Reason #3 - Dremio Catalog

Dremio supports external Apache Iceberg catalogs and offers its integrated catalog solutions, designed to streamline the management and governance of Iceberg tables. These catalog options make implementing and maintaining a robust Iceberg-based lakehouse architecture more accessible, whether your data resides in the cloud, on-premises, or a hybrid setup.

The Dremio Cloud Catalog, available as part of the Dremio Cloud platform, leverages the open-source Nessie catalog to provide Git-like version control for your Iceberg tables. This capability allows you to track changes, experiment with data safely, and roll back to previous states, fostering a collaborative and controlled data environment.

For organizations requiring a hybrid approach, Dremio offers the Dremio Hybrid Catalog, currently in private preview as part of the Dremio Software product. Built on Apache Polaris, this catalog can seamlessly track Iceberg tables across cloud and on-premises environments. This flexibility makes it ideal for enterprises navigating complex data infrastructures.

Both catalog solutions have powerful features to automate optimization and cleanup tasks for Iceberg tables, reducing operational burden. By integrating governance, performance optimization, and data tracking, Dremio Catalog simplifies the deployment of Iceberg-based lakehouses, ensuring your data is always well organized and ready for use.

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Conclusion

Dremio’s unique features and integrations make it the ultimate SQL query engine for Apache Iceberg tables. Its industry-leading raw performance, innovative query acceleration with Reflections, and powerful catalog options provide a seamless experience for managing and querying Iceberg tables across diverse data environments. These capabilities ensure you can handle modern analytics workloads quickly, consistently, and easily.

But that’s not all—Dremio offers even more reasons to make it your Iceberg SQL engine of choice. Features like COPY INTO simplify data loading by enabling you to copy data directly from files into Iceberg tables, while the Auto-ingest feature supports event-based file ingestion for real-time updates. These functionalities empower organizations to maintain agile and responsive data pipelines.

Additionally, Dremio integrates with leading tools like dbt, Monte Carlo, and others, enabling a scalable and maintainable data lakehouse infrastructure. These integrations help bridge the gap between data engineering, analytics, and governance, ensuring your data platform remains robust and future-ready.

With Dremio, you get a solution that goes beyond SQL queries—it’s a comprehensive platform for building and managing your Iceberg-powered data lakehouse with unmatched efficiency and flexibility.

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Read More about How Dremio and Iceberg Fit Together

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