Apache Hudi vs Delta Lake
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 use delta lake when building data pipelines that require reliable, high-quality data with features like data versioning, rollback capabilities, and schema evolution. Here's our take.
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
Apache Hudi
Nice PickDevelopers 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
Delta Lake
Developers should use Delta Lake when building data pipelines that require reliable, high-quality data with features like data versioning, rollback capabilities, and schema evolution
Pros
- +It is particularly valuable for scenarios involving streaming and batch data processing, machine learning workflows, and data lakehouse architectures where combining the scalability of data lakes with the reliability of data warehouses is essential
- +Related to: apache-spark, data-lake
Cons
- -Specific tradeoffs depend on your use case
The Verdict
Use Apache Hudi if: You want 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 and can live with specific tradeoffs depend on your use case.
Use Delta Lake if: You prioritize it is particularly valuable for scenarios involving streaming and batch data processing, machine learning workflows, and data lakehouse architectures where combining the scalability of data lakes with the reliability of data warehouses is essential over what Apache Hudi offers.
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
Disagree with our pick? nice@nicepick.dev