Botnets have evolved into intelligent and powerful cyber weapons, facilitating across-the-board cyberattacks and allowing them to achieve malicious purposes. Detecting botnets is a significant challenge due to their dynamic behavior and the increasing use of encryption and evasion strategies. These challenges increase because botnets continuously transform to remain undetected and bypass traditional security standards. Unlike previous reviews, which predominantly concentrate on individual detection techniques, this study provides a comprehensive comparative review of recent advancements in botnet detection. The review explores an exhaustive background on botnets, covering aspects such as Botnet propagation techniques and their lifecycle, Botnet architecture, and types, focusing on common attack methods. Furthermore, various botnet detection techniques are categorized and analyzed to establish a structured taxonomy. The review also categorizes botnet detection techniques according to their methodologies and presents a taxonomy highlighting their key characteristics. It also outlines their effectiveness, challenges, and performance metrics. This study serves as a reference point for cybersecurity researchers, offering valuable insights into the latest advancements and future research guidelines against evolving botnet threats.