SIEM vs. Security Analytics

Security Information and Event Management (SIEM) systems have historically been effective in identifying and managing threats through log data collection from various devices, but their limitations are becoming more evident due to the evolving IT landscape. Traditional SIEM systems are costly, time-consuming to implement, and were not designed to handle the vast data from modern CI/CD practices or cloud infrastructures. They primarily rely on rules-based or statistical approaches that struggle with new, undocumented threats and internal security issues. In contrast, next-generation SIEM platforms, based on Security Analytics, offer a proactive approach by leveraging cloud-based infrastructure, AI, and machine learning to analyze data from diverse sources, providing more flexible, scalable, and cost-effective security solutions. These platforms improve threat detection capabilities by continuously learning and adapting to new threats, thereby offering better protection for modern, distributed IT environments.