Apache Iceberg vs Apache Hudi

Developers should learn Apache Iceberg when building or modernizing data lakes to handle complex analytics, as it addresses common pain points like data consistency, schema changes, and performance at scale meets developers should learn apache hudi when building or managing data lakes that require real-time data ingestion, efficient upserts/deletes, and incremental processing for analytics. Here's our take.

Apache Iceberg

Nice Pick

Developers should learn Apache Iceberg when building or modernizing data lakes to handle complex analytics, as it addresses common pain points like data consistency, schema changes, and performance at scale

Pros

• It is particularly useful for use cases requiring reliable ETL/ELT pipelines, real-time analytics, and multi-engine access (e
• Related to: apache-spark, apache-hive

Cons

• Specific tradeoffs depend on your use case

Apache Hudi

Developers should learn Apache Hudi when building or managing data lakes that require real-time data ingestion, efficient upserts/deletes, and incremental processing for analytics

Pros

• It is particularly useful in scenarios like streaming ETL pipelines, real-time dashboards, and compliance-driven data management where data freshness and transactional consistency are critical
• Related to: apache-spark, apache-flink

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. Apache Iceberg is a database while Apache Hudi is a platform. We picked Apache Iceberg based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Apache Iceberg wins

Based on overall popularity. Apache Iceberg is more widely used, but Apache Hudi excels in its own space.