Maintaining an Apache Iceberg Lakehouse involves strategic optimization and vigilant governance across its core components—storage, data files, table formats, catalogs, and compute engines. Key tasks like partitioning, compaction, and clustering enhance performance, while regular maintenance such as expiring snapshots and removing orphan files helps manage storage and ensures compliance. Effective catalog management, whether through open-source or managed solutions like Dremio's Enterprise ...| Dremio
Migrating to an Apache Iceberg Lakehouse enhances data infrastructure with cost-efficiency, ease of use, and business value, despite the inherent challenges. By adopting a data lakehouse architecture, you gain benefits like ACID guarantees, time travel, and schema evolution, with Apache Iceberg offering unique advantages. Selecting the right catalog and choosing between in-place or shadow migration approaches, supported by a blue/green strategy, ensures a smooth transition. Tools like Dremio ...| Dremio
Integrating Snowflake with the Dremio Lakehouse Platform offers a powerful combination that addresses some of the most pressing challenges in data management today. By unifying siloed data, optimizing analytics costs, enabling self-service capabilities, and avoiding vendor lock-in, Dremio complements and extends the value of your Snowflake data warehouse.| Dremio
Dive into Apache Iceberg catalogs and their crucial role in evolving table usage and feature development in this comprehensive article.| Dremio
Select Apache Iceberg or Delta Lake’s UniForm based on business goals. The right infrastructure is vital for efficient data management and analysis.| Dremio