Apache Hudi vs Apache Iceberg

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 meets 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. Here's our take.

Apache Hudi

Nice Pick

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

Apache Iceberg

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

The Verdict

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

The Bottom Line

Apache Hudi wins

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