Postgres offers a powerful solution for optimizing query performance when dealing with complex multi-dimensional data sets, such as those involving both spatial and temporal dimensions. By utilizing the btree_gist extension, Postgres allows for the creation of indexes that integrate B-Tree and GiST index types, facilitating the efficient handling of queries that require searching across both one-dimensional and multi-dimensional data. This technique proves particularly useful in scenarios like analyzing UK crime data, where crimes are indexed by location and date, enabling significantly faster query times compared to using spatial or temporal indexing alone. The article demonstrates this with a practical example, highlighting the dramatic performance improvements achieved by implementing a combined space-and-time index, despite the trade-off in increased disk space usage. This approach not only enhances query speed but also broadens the applicability of indexing strategies to various combinations of data dimensions.