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When Doris Meets Iceberg: A Data Engineer's Redemption
- Apache Doris and Iceberg are transforming the way data lakes operate, offering faster queries, seamless schema evolution, and data consistency guarantees.
- The combination of Apache Doris and Iceberg provides a qualitative leap in data engineering, addressing issues like slow cross-source queries and complex schema changes.
- Apache Doris' lakehouse architecture enhancements in version 2.1 offer improved reading and writing capabilities for mainstream data lake formats and multi-SQL dialect compatibility.
- Doris native support for Iceberg features includes various Iceberg Catalog types, Iceberg table formats, snapshot history querying, time travel, and Iceberg table engine support.
- The integration of Doris and Iceberg simplifies lakehouse architectures, allowing for efficient data analysis, processing, and storage.
- Xiao Zhang's practical experiences with Doris + Iceberg highlight benefits like seamless schema evolution, data version management, and efficient catalog services.
- Doris combines the MPP engine with Iceberg for efficient data organization and storage optimization, enhancing performance.
- Operations and maintenance of Iceberg tables are streamlined through metric monitoring, snapshot management, and fault recovery methods.
- With Doris + Iceberg implementation, Xiao Zhang's data platform saw significant improvements in query performance, storage costs reduction, and operations efficiency.
- The integration of Doris and Iceberg continues to elevate data lakehouse capabilities, promising more benefits and advancements in data engineering.
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