Brendan Tierney provides an introduction to Apache Iceberg:
Modern data platforms increasingly separate compute from storage, using object stores as durable data lakes while scaling processing engines. Traditional “data lakes” built on Parquet files and Hive-style partitioning have limitations around atomicity, schema evolution, metadata scalability, and multi-engine interoperability. Apache Iceberg addresses these challenges by defining a high-performance table format with transactional guarantees, scalable metadata structures, and engine-agnostic semantics.
Apache Iceberg, an open-source table format that has become the industry standard for data sharing in modern data architectures. Let’s have a look at some of the key features, some of its limitations and a brief look at some of the alternatives.
Brendan explains where Iceberg fits in relation to data formats (e.g., Parquet, ORC, and Avro), as well as competitors like Delta Lake and Hudi.