Are you making the most of your Hadoop cluster?

Apache Hadoop, once a groundbreaking technology in the big data landscape, continues to be popular for processing vast amounts of data, thanks to its stability and active ecosystem. Its architecture combines compute and storage, making it ideal for on-premise, long-running batch analytics. However, as technology evolves, Hadoop's limitations, such as complexity, coupled compute-storage architecture, and security issues, have become more apparent, particularly in the cloud era. Many companies are now considering more modern solutions like data lakehouses, which offer the benefits of both data lakes and data warehouses, supporting a wide range of use cases with high performance and cost-efficiency. Apache Iceberg, an open table format for the cloud, is highlighted as a powerful option within the lakehouse architecture, providing enhanced features like updates, deletes, and schema evolution. Transitioning to a data lakehouse allows businesses to leverage legacy Hadoop systems while gradually adopting more versatile and efficient architectures, exemplified by solutions like Starburst's Icehouse, which combines the Iceberg format with the Trino SQL query engine for improved performance and cost savings.