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 maintaining data lakes that require robust data management, such as in scenarios involving frequent updates, schema changes, or multi-engine analytics. 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 maintaining data lakes that require robust data management, such as in scenarios involving frequent updates, schema changes, or multi-engine analytics

Pros

• It is particularly useful for use cases like real-time data ingestion, data warehousing on cloud storage, and ensuring data consistency across distributed queries, as it solves common issues like hidden partitions and slow metadata operations in traditional formats like Hive
• 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.