Modern Table Formats: Delta Lake vs Apache Iceberg vs Apache Hudi
Scenario context
Delta Lake, Apache Iceberg, and Apache Hudi are open table formats that wrap Parquet files with a transaction log (or snapshot tree) to deliver ACID guarantees, time travel, schema evolution, and efficient upserts on object storage.
🎯 System Scenario & Requirements
System Goal
Delta Lake, Apache Iceberg, and Apache Hudi are open table formats that wrap Parquet files with a transaction log (or snapshot tree) to deliver ACID guarantees, time travel, schema evolution, and efficient upserts on object storage.
Actors & Components
- Application or API tier
- Core service under design
- Operator or SRE observer
Functional Requirements
- Delta Lake, Apache Iceberg, and Apache Hudi are open table formats that wrap Parquet files with a transaction log (or snapshot tree) to deliver ACID guarantees, time travel, schema evolution, and efficient upserts on ob…
- Choose Delta Lake for Databricks/Spark-centric shops, Iceberg for multi-engine portability at petabyte scale, and Hudi for near-real-time CDC upserts and streaming pipelines.
- ---… This walkthrough focuses on What Production Data Teams Learn the Hard Way .
Constraints & Assumptions
- The source does not isolate a separate failure mode.
- Limits that matter for the scenario are called out in the stage decisions above.
⚡ Execution Stages & Decision Trace
Stage 1 — End-to-end outcome
Lesson 1: Compaction is not optional — it is a first-class pipeline job.
Lesson 1: Compaction is not optional — it is a first-class pipeline job.
Deep Dive
Scenario context
Delta Lake, Apache Iceberg, and Apache Hudi are open table formats that wrap Parquet files with a transaction log (or snapshot tree) to deliver ACID guarantees, time travel, schema evolution, and efficient upserts on object storage. Choose Delta Lake for Databricks/Spark-centric shops, Iceberg for multi-engine portability at petabyte scale, and Hudi for near-real-time CDC upserts and streaming pipelines.
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This…
This walkthrough focuses on Scenario context.
Before making a design choice, clarify:
- Delta Lake, Apache Iceberg, and Apache Hudi are open table formats that wrap Parquet files with a transaction log (or snapshot tree) to deliver ACID guarantees, time travel, schema evolution, and efficient upserts on ob…
- Choose Delta Lake for Databricks/Spark-centric shops, Iceberg for multi-engine portability at petabyte scale, and Hudi for near-real-time CDC upserts and streaming pipelines.
- ---… This walkthrough focuses on What Production Data Teams Learn the Hard Way .
Concepts in play: spark-data-engineering, data-warehousing-lakehouse, transaction-isolation-distributed-acid, database-sharding
Stage 1 — End-to-end outcome
- Lesson 1: Compaction is not optional — it is a first-class pipeline job.
Observable outcome: Lesson 1: Compaction is not optional — it is a first-class pipeline job.
End-to-end outcome
Delta Lake, Apache Iceberg, and Apache Hudi are open table formats that wrap Parquet files with a transaction log (or snapshot tree) to deliver ACID guarantees, time travel, schema evolution, and efficient upserts on object storage.
Alternatives considered
Alternatives considered
The source focuses on one primary design.
Failure and degraded modes
Failure and degraded modes
- Detection: The source does not isolate a separate failure mode.
- User or operator impact: The source does not isolate a separate failure mode.
Key learnings
- Lesson 1: Compaction is not optional — it is a first-class pipeline job.