Apache Iceberg

Apache Iceberg is an open-source table format created at Netflix. Its primary goal is to address the challenges of managing large datasets stored on distributed file systems like S3 or HDFS. Iceberg was designed to overcome the limitations of traditional table formats such as Hive, facilitating complex data modification and access operations while ensuring better transaction isolation due to:

• its native compatibility with SQL for reading and writing
• its ability to support full schema evolution
• its capability to handle massive datasets at the petabyte scale
• its fine-grained versioning with time travel and rollback features
• its guarantee of ACID transactions in a multi-user environment
• its scalable and efficient partitioning and compaction system for optimized read performance

Iceberg truly enables the datalakehouse paradigm, which structures a data lake to directly leverage its data.

However, it can make data pipelines more complex, particularly in terms of configuration, partition management, and maintenance—especially for teams unfamiliar with this format. Adopting Iceberg may require a steep learning curve for organizations that lack maturity in data lake management.

MDN’S POINT OF VIEW

Iceberg is at the heart of data trends in 2024. Initially developed at Netflix, this open-source table format is rapidly establishing itself as the interoperable file standard for managing tables in data lake architectures. If you are building your data lake today, you should consider it without hesitation.

THEODO’S POINT OF VIEW

At Theodo, we believe that Iceberg is an excellent solution for optimizing performance and storage in cases of high data volume. It appears to outperform alternatives like Delta Lake or Apache Hudi due to its flexibility in schema and partition evolution and better integration within modern architectures such as BigQuery or Snowflake.