The Importance of Dremio’s Hybrid Lakehouse Catalog
With the adoption of Apache Iceberg as the de facto table format for data lakes, the focus has shifted from choosing a table format to selecting the right lakehouse catalog. A lakehouse catalog is a directory for your Iceberg tables, enabling any analytics or data processing tool to discover and interact with those tables as if they were in a traditional data warehouse.
Many open-source catalog solutions exist today, such as Nessie, Apache Polaris (incubating), Apache Gravitino (incubating), Lakekeeper and more. These catalog solutions can be deployed and self-managed, allowing organizations to maintain control over their lakehouse environment. However, several critical challenges come with self-managed catalogs:
Management: Managing your own lakehouse catalog involves deployment complexity and ongoing infrastructure upkeep, demanding engineering resources for tasks like scaling, upgrading, and monitoring.
Table Management: Iceberg tables require regular maintenance for optimal performance. Table optimization tasks such as compaction, clustering, and snapshot expiration don’t happen automatically, so engineers are often left to determine the correct cadence for these operations manually.
Governance: In a lakehouse environment, governance has traditionally been handled at the engine level, which requires teams to reimplement governance policies across each tool. To address this, some catalogs have begun implementing portable governance features, reducing the redundancy of managing governance across tools.
Managing Tables Across Environments: Many organizations operate in hybrid or multi-cloud environments, which creates a need for catalogs that can seamlessly track and manage tables across cloud and on-premises environments.
Recognizing these challenges, Dremio Arctic pioneered the managed Iceberg catalog space by offering a fully managed, Nessie-based catalog integrated into the Dremio Cloud platform (Formerly Dremio Arctic, Now Dremio Cloud Catalog). Dremio Arctic provides automated governance, table management, and catalog-level branching and merging features. Following Dremio’s lead, other industry players have entered the managed Iceberg catalog market: Tabular (now part of Databricks, no longer accepting new customers), AWS Glue, BigQuery Catalog, Snowflake's Open Catalog, and others. Yet these solutions come with a significant limitation—they are designed exclusively for cloud environments, leaving organizations with hybrid cloud or on-prem data requirements underserved.
Introducing Dremio’s Hybrid Lakehouse Catalog
Dremio has recognized the need for a hybrid-friendly Iceberg catalog and is now launching the Dremio Hybrid Catalog, currently in private preview as part of the Dremio Software self-managed product. This catalog is unique and purpose-built to meet the demands of hybrid and on-prem environments in several ways:
Foundational Technology: Unlike Arctic, built on Nessie, Dremio Catalog intends to leverage Polaris as its foundational technology, providing a robust and scalable base for Iceberg catalog operations.
Support for Multi-Environment Storage Locations: Dremio Catalog is designed with hybrid cloud environments in mind, allowing organizations to manage Iceberg tables across multiple storage locations in both cloud and on-premises environments—all within a single catalog.
These enhancements make Dremio Catalog a powerful, flexible solution for organizations operating in complex hybrid environments, offering a seamlessly integrated Iceberg catalog that can manage and govern data efficiently.
Key Benefits of Dremio’s Hybrid Lakehouse Catalog
Dremio Catalog is purpose-built to address the primary challenges of managing Iceberg tables in hybrid and on-prem environments. Here’s how it delivers critical advantages over other catalog solutions:
Scalability and Manageability: Being part of the Dremio platform, Dremio Catalog provides a scalable, manageable Iceberg catalog that can be deployed anywhere. This allows organizations to enjoy all the benefits of a high-performance Iceberg catalog without the complexity of a self-managing catalog and query engine independently.
Automated Table Optimization: Dremio Catalog includes automated table optimization features, reducing the burden on engineers to schedule and manage table operations manually. Dremio handles compaction and snapshot expiration tasks, ensuring that Iceberg tables remain performant without constant manual intervention.
Built-In Governance: The catalog provides a centralized governance layer for Iceberg tables, enabling consistent governance policies across all tools connected to Dremio Catalog (Snowflake, Apache Spark, etc.). This eliminates the need for multiple governance implementations and ensures data security and compliance are maintained across the lakehouse ecosystem.
Unified Catalog Across Environments: Dremio Catalog can span multiple storage environments, making it easy to track and manage tables across cloud and on-premises locations. This feature is invaluable for hybrid and multi-cloud architectures, allowing organizations to achieve a unified view of their data lakehouse assets.
A Future-Proof Lakehouse Catalog Solution
The hybrid catalog offering from Dremio addresses a significant gap in the industry, especially as more organizations adopt hybrid and multi-cloud strategies. With Dremio Hybrid Catalog, organizations gain the flexibility to manage and govern Iceberg tables wherever their data resides, breaking free from the limitations of cloud-only catalogs.
Getting Started with Dremio’s Hybrid Lakehouse Catalog
While Dremio Catalog is currently available in private preview