In this course, we’ll explore how Hive revolutionized data management, its limitations, and why Apache Iceberg ( ) is the solution. Hive, created by Facebook in 2008, simplified data manipulation with SQL-like queries on Hadoop. However, it struggled with unstructured data and complex queries, making it less efficient for modern data needs. Apache Iceberg, introduced in 2016, addresses these issues by offering a unified query language and better support for unstructured and semi-structured data. With Iceberg’s columnar storage formats like Parquet, performance is improved, reducing I/O time while maintaining fast query speeds. For more resources on Data Lakehouses ( ), visit Dremio’s tutorials and community. Want to learn more? Visit our site or connect with us on social: Site: LinkedIn: Facebook: Twitter GitHub: