Graph analytics has a long history dating back to Leonhard Euler's solution of the "Seven Bridges of Königsberg" problem in 1736. However, it wasn't until recent years that graph technologies have seen an explosion of interest and usage. This growth is driven by several forces, including real-world applications of graph analytics, digitization, and advances in computing power. The convergence of analytics with transactions, also known as "translytics," enables organizations to better understand real-world networks and forecast their behaviors. Graph analytics are particularly useful for handling connected data and responsive to dynamic changes, which is why businesses are turning to them to improve predictive capabilities and decision-making frameworks for artificial intelligence. The integration of graph technologies with traditional OLAP and OLTP systems, such as HTAP, enables continual analysis to become ingrained in regular operations, leading to new forms of real-time business-driven decision-making processes.