The continuation of the Elasticsearch SQL series delves into more advanced features of Elasticsearch's SQL capabilities, building on the initial introduction of its SQL feature and _translate API. The article explores complex functionalities like GROUP BY using Composite Aggregation, which allows scalable data grouping without memory limitations and filtering groups with the HAVING operator. It highlights the use of the QUERY and MATCH operators to leverage Elasticsearch's unique text search capabilities, allowing more nuanced searches compared to traditional RDBMS systems. It also discusses cross-index searches using aliases, illustrating how queries can span multiple indices with identical mappings. While Elasticsearch SQL currently lacks traditional JOIN support, it can handle nested documents, offering some degree of relational modeling. The article concludes by mentioning current limitations in cross-index queries and nested SELECT clauses, while hinting at future improvements such as multi-level GROUP BY, geospatial operators, and enhanced date/time functions, showcasing the ongoing evolution of Elasticsearch SQL.