What It Is
Apache Iceberg sits between files in object storage and the engines that query them, tracking table contents through metadata. It gives data lakes features once found mainly in databases.
Key Points
- ACID transactions: readers and writers work together without corrupting data.
- Schema evolution: columns can change without rewriting tables.
- Time travel: query a table as it existed at an earlier moment.
- Engine-neutral: Spark, Flink, Trino, Snowflake, and others share the same tables.
Why It Matters
Open formats reduce vendor lock-in and keep data portable. Compaction keeps queries fast as small files accumulate. Features such as snapshot isolation let analysts query a table while pipelines update it, so reporting stays consistent.
How ClearLeaff Applies It
We build lakehouse architectures on Iceberg, alongside Snowflake and Delta Lake, to unify real-time and batch workloads in one governed platform.