Apache Hudi vs Apache Iceberg
A side-by-side comparison of two Data Storage Optimisation AI agents — to help you pick the right one.
Apache Hudi
Apache Hudi is an open-source data lake platform that enables incremental data processing and upserts on large-scale datasets. It provides transactional capabilities typically found in databases directly on data lakes, supporting both batch and streaming workflows. Hudi integrates with popular query engines like Spark, Flink, and Presto for efficient data access.
Apache Iceberg
Apache Iceberg is an open table format designed for large-scale analytics workloads, enabling ACID transactions, schema evolution, and efficient metadata management. It provides cross-engine compatibility, allowing tools like Spark, Trino, and Flink to work concurrently on the same datasets without conflicts.
| Apache Hudi | Apache Iceberg | |
|---|---|---|
| Category | Data Storage Optimisation | Data Storage Optimisation |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Skill level | Intermediate | Intermediate |
| Pricing | Open Source | Open Source |
Apache Hudi: what it solves
Hudi solves the challenge of performing efficient updates, deletes, and incremental processing on immutable data lake storage, which traditionally lacks these database-like capabilities.
Apache Iceberg: what it solves
It solves the challenge of maintaining data consistency and performance in distributed analytics environments where multiple engines need to access and modify the same datasets.