This review comprehensively examines the state-of-the-art research on two-dimensional (2D) material-based memristive arrays, focusing on critical aspects such as material selection, device performance metrics, array structures, and potential applications. It highlights the advantages of 2D materials, including low switching voltage, reduced power consumption, and the ability to form heterojunctions. The review discusses various switching mechanisms, such as conductive filament formation, vacancy migration, photon response, phase change, and ferroelectricity, and their impact on device performance. Key performance metrics, including programming energy, program voltage, endurance, retention, device-to-device variation, and cycle-to-cycle variation, are evaluated for both artificial synapses and artificial neurons. The review also addresses the challenges in progressing from single-device characterization to array-level and system-level implementations, along with proposed solutions. The primary objective is to bridge the gap between single-device characterization and the realization of next-generation in-memory computing using 2D material-based memristive devices.This review comprehensively examines the state-of-the-art research on two-dimensional (2D) material-based memristive arrays, focusing on critical aspects such as material selection, device performance metrics, array structures, and potential applications. It highlights the advantages of 2D materials, including low switching voltage, reduced power consumption, and the ability to form heterojunctions. The review discusses various switching mechanisms, such as conductive filament formation, vacancy migration, photon response, phase change, and ferroelectricity, and their impact on device performance. Key performance metrics, including programming energy, program voltage, endurance, retention, device-to-device variation, and cycle-to-cycle variation, are evaluated for both artificial synapses and artificial neurons. The review also addresses the challenges in progressing from single-device characterization to array-level and system-level implementations, along with proposed solutions. The primary objective is to bridge the gap between single-device characterization and the realization of next-generation in-memory computing using 2D material-based memristive devices.