Apache Druid 26.0 introduces several new features aimed at enhancing real-time analytics capabilities, including schema auto-discovery, shuffle joins, and support for UNNEST SQL commands and array data types. Schema auto-discovery enables automatic detection and adaptation to schema changes, reducing manual effort and improving data quality, while shuffle joins allow for efficient processing of large data sets by partitioning and reshuffling data across multiple nodes. The UNNEST SQL command facilitates the handling of nested arrays by converting them into individual rows, enhancing data manipulation possibilities. Additionally, the introduction of an array data type supports storing multiple values in a single column, thereby simplifying queries and calculations while accommodating variable-length data. These advancements aim to improve the performance, flexibility, and scalability of data processing within Druid, making it more adaptable for diverse and complex data analytics tasks.