Apache Iceberg
Apache Iceberg is an open-source table format for managing large-scale analytic datasets in data lakes, designed to bring reliability, performance, and scalability to big data workloads. It provides ACID transactions, schema evolution, and time travel capabilities, enabling efficient querying and management of petabyte-scale data across engines like Spark, Trino, and Flink. By abstracting the underlying storage, it ensures data consistency and simplifies operations in cloud object stores like S3 or Azure Blob Storage.
Developers should learn Apache Iceberg when building or modernizing data lakes to handle complex analytics, as it addresses common pain points like data consistency, schema changes, and performance at scale. It is particularly useful for use cases requiring reliable ETL/ELT pipelines, real-time analytics, and multi-engine access (e.g., combining batch and streaming processing), making it ideal for enterprises with large, evolving datasets in cloud environments.