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Apache Iceberg vs Delta Lake vs Hudi: Choosing the Right Open Table Format

There isn't a universal winner. The real architectural question is: what does your enterprise need five years from now?

6 min read

There isn't a universal winner. Modern data platforms increasingly need an open table format that can support ACID transactions, schema evolution, streaming, CDC, governance, and multiple processing engines.

The real architectural question is: what does your enterprise need five years from now?
  • 🧊 Iceberg — a strong choice for open, multi-engine architectures.
  • ⚡ Delta Lake — compelling for mature lakehouse and Databricks-centric workloads.
  • 🔥 Hudi — particularly useful for incremental processing and high-volume upserts.

At Karsient, we believe table-format selection should start with business workload and target architecture — not technology hype.

Architecture insight

Choose Iceberg when interoperability across Spark, Trino, Flink, Snowflake, and other engines is a priority.

Choose Delta Lake when you need mature ACID transactions, governance, streaming + batch convergence, and a strong Databricks lakehouse architecture.

Choose Hudi when your platform is heavily driven by CDC, upserts, and incremental processing.

Our perspective

Don't select a table format because it's trending. Select it based on:

Workload
Engines
Governance
CDC
Performance
Cost
Future architecture
Architecture beats hype.
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