Lakehouse Table Formats 2026: Iceberg, Delta, Hudi, Paimon, DuckLake

The table format war has effectively ended with Apache Iceberg emerging as the industry's interoperability standard, adopted natively by every major cloud, Snowflake, Databricks, and even DuckDB. But that convergence hasn't erased the other formats, each still serves a distinct design center: Delta Lake anchors the largest single-vendor ecosystem, Apache Hudi's 1.0 milestone pushes toward database-grade indexing, Apache Paimon owns streaming-native table design, and DuckLake questions whether metadata management has grown needlessly complex.

This piece breaks down, as of July 2026, how each format's mechanics actually work, from Iceberg's snapshot tree and manifest lists to Delta's transaction-log model and UniForm bridging, along with current release states, ecosystem adoption, governance structures, and roadmap direction, including Iceberg's contested v4 design cycle targeting streaming-rate writes and AI-scale wide tables.

For engineers, the takeaway is that format choice is no longer purely a compatibility question. It's an architectural decision shaped by workload shape, batch versus streaming, upsert-heavy ingestion, or wide AI-scale tables, and by how much operational complexity a team is willing to own.