Apache Iceberg vs Delta Lake

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 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 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

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

These tools serve different purposes. Apache Iceberg is a database while Delta Lake 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 Delta Lake excels in its own space.